Publications

Bibtex is available by clicking on the link beneath each publication. A Bibtex file containing all of our publications is available here.

2015

  • [DOI] M. Ashtari, H. Zhang, P. A. Cook, L. L. Cyckowski, K. S. Shindler, K. A. Marshall, P. Aravand, A. Vossough, J. C. Gee, A. Maguire, C. I. Baker, and J. Bennett, “Plasticity of the human visual system after retinal gene therapy in patients with Leber’s congenital amaurosis.,” Sci Transl Med, vol. 7, iss. 296, p. 296ra110, 2015.
    [Bibtex]
    @ARTICLE{Ashtari2015STM,
    author = {Ashtari, Manzar and Zhang, Hui and Cook, Philip A. and Cyckowski,
    Laura L. and Shindler, Kenneth S. and Marshall, Kathleen A. and Aravand,
    Puya and Vossough, Arastoo and Gee, James C. and Maguire, Albert
    M. and Baker, Chris I. and Bennett, Jean},
    title = {{P}lasticity of the human visual system after retinal gene therapy
    in patients with {L}eber's congenital amaurosis.},
    journal = {{S}ci {T}ransl {M}ed},
    year = {2015},
    volume = {7},
    pages = {296ra110},
    number = {296},
    month = {Jul},
    __markedentry = {[pcook:6]},
    abstract = {Much of our knowledge of the mechanisms underlying plasticity in the
    visual cortex in response to visual impairment, vision restoration,
    and environmental interactions comes from animal studies. We evaluated
    human brain plasticity in a group of patients with Leber's congenital
    amaurosis (LCA), who regained vision through gene therapy. Using
    non-invasive multimodal neuroimaging methods, we demonstrated that
    reversing blindness with gene therapy promoted long-term structural
    plasticity in the visual pathways emanating from the treated retina
    of LCA patients. The data revealed improvements and normalization
    along the visual fibers corresponding to the site of retinal injection
    of the gene therapy vector carrying the therapeutic gene in the treated
    eye compared to the visual pathway for the untreated eye of LCA patients.
    After gene therapy, the primary visual pathways (for example, geniculostriate
    fibers) in the treated retina were similar to those of sighted control
    subjects, whereas the primary visual pathways of the untreated retina
    continued to deteriorate. Our results suggest that visual experience,
    enhanced by gene therapy, may be responsible for the reorganization
    and maturation of synaptic connectivity in the visual pathways of
    the treated eye in LCA patients. The interactions between the eye
    and the brain enabled improved and sustained long-term visual function
    in patients with LCA after gene therapy.},
    doi = {10.1126/scitranslmed.aaa8791},
    institution = {{C}enter for {A}dvanced {R}etinal and {O}cular {T}herapeutics, {U}niversity
    of {P}ennsylvania {P}erelman {S}chool of {M}edicine, 309 {S}tellar-{C}hance
    {L}abs, 422 {C}urie {B}oulevard, {P}hiladelphia, {PA} 19104, {USA}.
    {F}.{M}. {K}irby {C}enter for {M}olecular {O}phthalmology, {S}cheie
    {E}ye {I}nstitute, {D}epartment of {O}phthalmology, {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {PA} 19014, {USA}. {C}enter for
    {C}ellular and {M}olecular {T}herapeutics at {T}he {C}hildren's {H}ospital
    of {P}hiladelphia, {C}olket {T}ranslational {R}esearch {B}uilding,
    3501 {C}ivic {C}enter {B}oulevard, {P}hiladelphia, {PA} 19014, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {7/296/296ra110},
    pmid = {26180100},
    timestamp = {2016.01.04},
    url = {http://dx.doi.org/10.1126/scitranslmed.aaa8791}
    }
  • B. B. Avants, J. T. Duda, E. Kilroy, K. Krasileva, K. Jann, B. T. Kandel, N. Tustison, L. Yan, M. Jog, R. Smith, Y. Wang, M. Dapretto, and D. J. J. Wang, “The pediatric template of brain perfusion,” Scientific Data, vol. 2, iss. 150003, p. EP -, 2015.
    [Bibtex]
    @ARTICLE{Avants2015SD,
    author = {Avants, Brian B and Duda, Jeffrey T and Kilroy, Emily and Krasileva,
    Kate and Jann, Kay and Kandel, Benjamin T and Tustison, Nicholas
    J and Yan, Lirong and Jog, Mayank and Smith, Robert and Wang, Yi
    and Dapretto, Mirella and Wang, Danny J J},
    title = {{T}he pediatric template of brain perfusion},
    journal = {{S}cientific {D}ata},
    year = {2015},
    volume = {2},
    pages = {EP -},
    number = {150003},
    month = {02},
    abstract = {Magnetic resonance imaging (MRI) captures the dynamics of brain development
    with multiple modalities that quantify both structure and function.
    These measurements may yield valuable insights into the neural patterns
    that mark healthy maturation or that identify early risk for psychiatric
    disorder. The Pediatric Template of Brain Perfusion (PTBP) is a free
    and public neuroimaging resource that will help accelerate the understanding
    of childhood brain development as seen through the lens of multiple
    modality neuroimaging and in relation to cognitive and environmental
    factors. The PTBP uses cross-sectional and longitudinal MRI to quantify
    cortex, white matter, resting state functional connectivity and brain
    perfusion, as measured by Arterial Spin Labeling (ASL), in 120 children
    7–18 years of age. We describe the PTBP and show, as a demonstration
    of validity, that global summary measurements capture the trajectories
    that demarcate critical turning points in brain maturation. This
    novel resource will allow a more detailed understanding of the network-level,
    structural and functional landmarks that are obtained during normal
    adolescent brain development.},
    bdsk-url-1 = {http://dx.doi.org/10.1038/sdata.2015.3},
    date = {2015/02/03/online},
    date-added = {2015-05-08 15:13:03 +0000},
    date-modified = {2015-05-08 15:13:03 +0000},
    day = {03},
    l3 = {10.1038/sdata.2015.3; http://www.nature.com/articles/sdata20153#supplementary-information},
    m3 = {Data Descriptor},
    owner = {jtduda},
    publisher = {Macmillan Publishers Limited SN -},
    timestamp = {2015.05.08},
    ty = {JOUR},
    url = {http://dx.doi.org/10.1038/sdata.2015.3}
    }
  • [DOI] M. Kumar, J. Duda, S. Y. Yoon, J. Bagel, P. O’Donnell, C. Vite, S. Pickup, J. C. Gee, J. W. H. Wolfe, and H. Poptani, “Diffusion Tensor Imaging for Assessing Brain Gray and White Matter Abnormalities in a Feline Model of \alpha-Mannosidosis,” Journal of Neuropathology & Experimental Neurology, 2015.
    [Bibtex]
    @ARTICLE{Kumar2015,
    author = {Kumar, Manoj and Duda, Jeffrey and Yoon, Sea Young and Bagel, Jessica
    and O'Donnell, Patricia and Vite, Charles and Pickup, Stephen and
    Gee, James C. and Wolfe, John H. Wolfe and Poptani, H.Harish},
    title = {{D}iffusion {T}ensor {I}maging for {A}ssessing {B}rain {G}ray and
    {W}hite {M}atter {A}bnormalities in a {F}eline {M}odel of \alpha-{M}annosidosis},
    journal = {{J}ournal of {N}europathology \& {E}xperimental {N}eurology},
    year = {2015},
    doi = {10.1093/jnen/nlv007},
    owner = {jtduda},
    timestamp = {2015.12.16}
    }
  • [DOI] T. D. Satterthwaite, P. A. Cook, S. E. Bruce, C. Conway, E. Mikkelsen, E. Satchell, S. N. Vandekar, T. Durbin, R. T. Shinohara, and Y. I. Sheline, “Dimensional depression severity in women with major depression and post-traumatic stress disorder correlates with fronto-amygdalar hypoconnectivty.,” Mol Psychiatry, 2015.
    [Bibtex]
    @ARTICLE{Satterthwaite2015MP,
    author = {Satterthwaite, T. D. and Cook, P. A. and Bruce, S. E. and Conway,
    C. and Mikkelsen, E. and Satchell, E. and Vandekar, S. N. and Durbin,
    T. and Shinohara, R. T. and Sheline, Y. I.},
    title = {{D}imensional depression severity in women with major depression
    and post-traumatic stress disorder correlates with fronto-amygdalar
    hypoconnectivty.},
    journal = {{M}ol {P}sychiatry},
    year = {2015},
    month = {Sep},
    __markedentry = {[pcook:6]},
    abstract = {Depressive symptoms are common in multiple psychiatric disorders and
    are frequent sequelae of trauma. A dimensional conceptualization
    of depression suggests that symptoms should be associated with a
    continuum of deficits in specific neural circuits. However, most
    prior investigations of abnormalities in functional connectivity
    have typically focused on a single diagnostic category using hypothesis-driven
    seed-based analyses. Here, using a sample of 105 adult female participants
    from three diagnostic groups (healthy controls, n=17; major depression,
    n=38; and post-traumatic stress disorder, n=50), we examine the dimensional
    relationship between resting-state functional dysconnectivity and
    severity of depressive symptoms across diagnostic categories using
    a data-driven analysis (multivariate distance-based matrix regression).
    This connectome-wide analysis identified foci of dysconnectivity
    associated with depression severity in the bilateral amygdala. Follow-up
    seed analyses using subject-specific amygdala segmentations revealed
    that depression severity was associated with amygdalo-frontal hypo-connectivity
    in a network of regions including bilateral dorsolateral prefrontal
    cortex, anterior cingulate and anterior insula. In contrast, anxiety
    was associated with elevated connectivity between the amygdala and
    the ventromedial prefrontal cortex. Taken together, these results
    emphasize the centrality of the amygdala in the pathophysiology of
    depressive symptoms, and suggest that dissociable patterns of amygdalo-frontal
    dysconnectivity are a critical neurobiological feature across clinical
    diagnostic categories.Molecular Psychiatry advance online publication,
    29 September 2015; doi:10.1038/mp.2015.149.},
    doi = {10.1038/mp.2015.149},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania {P}erelman
    {S}chool of {M}edicine, {P}hiladelphia, {PA}, {USA}.},
    language = {eng},
    medline-pst = {aheadofprint},
    owner = {pcook},
    pii = {mp2015149},
    pmid = {26416545},
    timestamp = {2016.01.04},
    url = {http://dx.doi.org/10.1038/mp.2015.149}
    }

2014 (Oral presentation)

  • J. Wu, M. Ashtari, L. M. Betancourt, N. L. Brodsky, J. Giannetta, J. Gee, H. Hurt, and B. Avants, “Cortical Parcellation for Neonatal Brains,” in IEEE 11th International Symposium on Biomedical Imaging, Beijing, China, 2014 (Oral presentation).
    [Bibtex]
    @CONFERENCE{WuISBI2014,
    author = {Jue Wu and Manzar Ashtari and Laura M. Betancourt and Nancy L. Brodsky
    and Joan Giannetta and James Gee and Hallam Hurt and Brian Avants},
    title = {{C}ortical {P}arcellation for {N}eonatal {B}rains},
    booktitle = {{IEEE} 11th {I}nternational {S}ymposium on {B}iomedical {I}maging},
    year = {2014 (Oral presentation)},
    address = {Beijing, China},
    month = {April},
    owner = {johnwoo},
    timestamp = {2014.02.11}
    }

2014

  • [DOI] D. H. Adler, J. Pluta, S. Kadivar, C. Craige, J. C. Gee, B. B. Avants, and P. Yushkevich, “Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI,” Neuroimage, vol. 84, iss. 1, pp. 505-523, 2014.
    [Bibtex]
    @ARTICLE{Adler2014N,
    author = {Adler, Daniel H. and Pluta, John and Kadivar, Salmon and Craige,
    Caryne and Gee, James C. and Avants, Brian B. and Yushkevich, Paul
    A.},
    title = {{H}istology-derived volumetric annotation of the human hippocampal
    subfields in postmortem {MRI}},
    journal = {{N}euroimage},
    year = {2014},
    volume = {84},
    pages = {505--523},
    number = {1},
    month = {Jan},
    doi = {http://dx.doi.org/10.1016/j.neuroimage.2013.08.067}
    }
  • L. M. Betancourt, N. L. Brodsky, J. Wu, B. Avants, M. Farah, and H. Hurt, “Is There an Effect of Socioeconomic Status (SES) on Infant Neural Development at Age 1 Month?,” in Proc. 2014 Pediatric Academic Societies, Vancouver, Canada, 2014.
    [Bibtex]
    @CONFERENCE{BetancourtPAS2014,
    author = {Laura M. Betancourt and Nancy L. Brodsky and Jue Wu and Brian Avants
    and Martha Farah and Hallam Hurt},
    title = {{I}s {T}here an {E}ffect of {S}ocioeconomic {S}tatus ({SES}) on {I}nfant
    {N}eural {D}evelopment at {A}ge 1 {M}onth?},
    booktitle = {{P}roc. 2014 {P}ediatric {A}cademic {S}ocieties, {V}ancouver, {C}anada},
    year = {2014},
    owner = {johnwoo},
    timestamp = {2014.02.12}
    }
  • [DOI] P. A. Cook, C. T. McMillan, B. B. Avants, J. E. Peelle, J. C. Gee, and M. Grossman, “Relating brain anatomy and cognitive ability using a multivariate multimodal framework.,” Neuroimage, vol. 99, pp. 477-486, 2014.
    [Bibtex]
    @ARTICLE{Cook2014N,
    author = {Cook, Philip A. and McMillan, Corey T. and Avants, Brian B. and Peelle,
    Jonathan E. and Gee, James C. and Grossman, Murray},
    title = {{R}elating brain anatomy and cognitive ability using a multivariate
    multimodal framework.},
    journal = {{N}euroimage},
    year = {2014},
    volume = {99},
    pages = {477--486},
    month = {Oct},
    abstract = {Linking structural neuroimaging data from multiple modalities to cognitive
    performance is an important challenge for cognitive neuroscience.
    In this study we examined the relationship between verbal fluency
    performance and neuroanatomy in 54 patients with frontotemporal degeneration
    (FTD) and 15 age-matched controls, all of whom had T1- and diffusion-weighted
    imaging. Our goal was to incorporate measures of both gray matter
    (voxel-based cortical thickness) and white matter (fractional anisotropy)
    into a single statistical model that relates to behavioral performance.
    We first used eigenanatomy to define data-driven regions of interest
    (DD-ROIs) for both gray matter and white matter. Eigenanatomy is
    a multivariate dimensionality reduction approach that identifies
    spatially smooth, unsigned principal components that explain the
    maximal amount of variance across subjects. We then used a statistical
    model selection procedure to see which of these DD-ROIs best modeled
    performance on verbal fluency tasks hypothesized to rely on distinct
    components of a large-scale neural network that support language:
    category fluency requires a semantic-guided search and is hypothesized
    to rely primarily on temporal cortices that support lexical-semantic
    representations; letter-guided fluency requires a strategic mental
    search and is hypothesized to require executive resources to support
    a more demanding search process, which depends on prefrontal cortex
    in addition to temporal network components that support lexical representations.
    We observed that both types of verbal fluency performance are best
    described by a network that includes a combination of gray matter
    and white matter. For category fluency, the identified regions included
    bilateral temporal cortex and a white matter region including left
    inferior longitudinal fasciculus and frontal-occipital fasciculus.
    For letter fluency, a left temporal lobe region was also selected,
    and also regions of frontal cortex. These results are consistent
    with our hypothesized neuroanatomical models of language processing
    and its breakdown in FTD. We conclude that clustering the data with
    eigenanatomy before performing linear regression is a promising tool
    for multimodal data analysis.},
    doi = {10.1016/j.neuroimage.2014.05.008},
    institution = {{P}enn {F}rontotemporal {D}egeneration {C}enter, {D}epartment of
    {N}eurology, {P}erelman {S}chool of {M}edicine, {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {PA} 19104, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S1053-8119(14)00373-5},
    pmid = {24830834},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2014.05.008}
    }
  • P. A. Cook, P. A. Yushkevich, S. Tian, S. Luz, S. Bhatnagar, and J. C. Gee, “Structure Specific Analysis of white and gray matter in the rat brain after exposure to chronic stress,” in Proceedings 22nd Scientific Meeting, International Society for Magnetic Resonance in Medicine, Milan, Italy, 2014, p. 4554.
    [Bibtex]
    @INPROCEEDINGS{Cook2014ISMRM,
    author = {Cook, Philip A. and Yushkevich, Paul A. and Tian, Sijie and Luz,
    Sandra and Bhatnagar, Seema and Gee, James C.},
    title = {{S}tructure {S}pecific {A}nalysis of white and gray matter in the
    rat brain after exposure to chronic stress},
    booktitle = {{P}roceedings 22nd {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {M}ilan, {I}taly},
    year = {2014},
    pages = {4554},
    abstract = {Language deficits are widely reported in frontotemporal dementia (FTD),
    including non-fluent primary progressive aphasia (naPPA), semantic-variant
    primary progressive aphasia (svPPA) behavioral variant FTD (bvFTD).
    We hypothesize that these deficits are due to disruption of a large-scale
    neural network involving both language and executive resources. Here
    we use multi-modal MRI and sparse statistical methods to evaluate
    whether imaging of white matter (WM) with diffusion MRI enhances
    prediction of the neuroanatomic basis for their deficit when combined
    with cortical thickness derived from T1 MRI.},
    keywords = {SLC1011},
    owner = {pcook},
    timestamp = {2014.03.13}
    }
  • [DOI] J. T. Duda, P. A. Cook, and J. C. Gee, “Reproducibility of graph metrics of human brain structural networks.,” Front Neuroinform, vol. 8, p. 46, 2014.
    [Bibtex]
    @ARTICLE{Duda2014FNIF,
    author = {Duda, Jeffrey T. and Cook, Philip A. and Gee, James C.},
    title = {{R}eproducibility of graph metrics of human brain structural networks.},
    journal = {{F}ront {N}euroinform},
    year = {2014},
    volume = {8},
    pages = {46},
    abstract = {Recent interest in human brain connectivity has led to the application
    of graph theoretical analysis to human brain structural networks,
    in particular white matter connectivity inferred from diffusion imaging
    and fiber tractography. While these methods have been used to study
    a variety of patient populations, there has been less examination
    of the reproducibility of these methods. A number of tractography
    algorithms exist and many of these are known to be sensitive to user-selected
    parameters. The methods used to derive a connectivity matrix from
    fiber tractography output may also influence the resulting graph
    metrics. Here we examine how these algorithm and parameter choices
    influence the reproducibility of proposed graph metrics on a publicly
    available test-retest dataset consisting of 21 healthy adults. The
    dice coefficient is used to examine topological similarity of constant
    density subgraphs both within and between subjects. Seven graph metrics
    are examined here: mean clustering coefficient, characteristic path
    length, largest connected component size, assortativity, global efficiency,
    local efficiency, and rich club coefficient. The reproducibility
    of these network summary measures is examined using the intraclass
    correlation coefficient (ICC). Graph curves are created by treating
    the graph metrics as functions of a parameter such as graph density.
    Functional data analysis techniques are used to examine differences
    in graph measures that result from the choice of fiber tracking algorithm.
    The graph metrics consistently showed good levels of reproducibility
    as measured with ICC, with the exception of some instability at low
    graph density levels. The global and local efficiency measures were
    the most robust to the choice of fiber tracking algorithm.},
    doi = {10.3389/fninf.2014.00046},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {D}epartment
    of {R}adiology, {U}niversity of {P}ennsylvania {P}hiladelphia, {PA},
    {USA}.},
    language = {eng},
    medline-pst = {epublish},
    owner = {jtduda},
    pmid = {24847245},
    timestamp = {2014.05.30},
    url = {http://dx.doi.org/10.3389/fninf.2014.00046}
    }
  • [DOI] A. S. Jassar, M. M. Levack, R. Solorzano, A. M. Pouch, G. Ferrari, A. Cheung, V. A. Ferrari, J. H. Gorman 3rd, R. Gorman, and B. M. Jackson, “Feasibility of In Vivo Human Aortic Valve Modeling Using Real-Time Three-Dimensional Echocardiography.,” Ann Thorac Surg, 2014.
    [Bibtex]
    @ARTICLE{Jassar2014ATS,
    author = {Jassar, Arminder S. and Levack, Melissa M. and Solorzano, Ricardo
    D. and Pouch, Alison M. and Ferrari, Giovanni and Cheung, Albert
    T. and Ferrari, Victor A. and Gorman, 3rd, Joseph H and Gorman, Robert
    C. and Jackson, Benjamin M.},
    title = {{F}easibility of {I}n {V}ivo {H}uman {A}ortic {V}alve {M}odeling
    {U}sing {R}eal-{T}ime {T}hree-{D}imensional {E}chocardiography.},
    journal = {{A}nn {T}horac {S}urg},
    year = {2014},
    month = {Feb},
    abstract = {Surgical techniques for aortic valve (AV) repair are directed toward
    restoring normal structural relationships in the aortic root and
    rely on detailed assessment of root and valve anatomy. Noninvasive
    three-dimensional (3D) imaging and modeling may assist in patient
    selection and operative planning.Transesophageal real-time 3D echocardiographic
    images of 5 patients with normal AV were acquired. The aortic root
    and the annulus were manually segmented at end diastole using a 36-point
    rotational template. The AV leaflets and the coaptation zone were
    manually segmented in parallel 1-mm cross sections. Quantitative
    3D models of the AV and root were generated and used to measure standard
    anatomic parameters and were compared to conventional two-dimensional
    echocardiographic measurements. All measurements are given as mean
    ± SD.Annular, sinus, and sinotubular junction areas were 4.1 ± 0.6
    cm(2), 7.5 ± 1.2 cm(2), and 3.9 ± 1.0 cm(2), respectively. Root diameters
    (measured in three locations) by 3D model inspection and two-dimensional
    echocardiography measurement correlated (R(2) = 0.75). Noncoapted
    areas of the left, right, and noncoronary leaflets were 1.9 ± 0.2
    cm(2), 1.6 ± 0.3 cm(2), and 1.6 ± 0.3 cm(2), respectively. Mean coaptation
    areas for the left-right, left-noncoronary, and right-noncoronary
    coaptation zones were 87.7 ± 36.9 mm(2), 69.9 ± 20.7 mm(2), and 114.2
    ± 23.0 mm(2), respectively. The mean ratio of noncoapted leaflet
    area to annular area was 1.3 ± 0.2.High-resolution 3D models of the
    in vivo normal human aortic root and valve were generated using 3D
    echocardiography. Quantitative 3D models and analysis may assist
    in characterization of pathology and decision making for AV repair.},
    doi = {10.1016/j.athoracsur.2013.12.017},
    institution = {{D}epartment of {S}urgery, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {P}ennsylvania. {E}lectronic address: benjamin.jackson@uphs.upenn.edu.},
    language = {eng},
    medline-pst = {aheadofprint},
    owner = {alison},
    pii = {S0003-4975(13)02852-X},
    pmid = {24518577},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.athoracsur.2013.12.017}
    }
  • [DOI] C. T. McMillan, B. B. Avants, P. Cook, L. Ungar, J. Q. Trojanowski, and M. Grossman, “The power of neuroimaging biomarkers for screening frontotemporal dementia.,” Hum Brain Mapp, vol. 35, iss. 9, pp. 4827-4840, 2014.
    [Bibtex]
    @ARTICLE{McMillan2014HBM,
    author = {McMillan, Corey T. and Avants, Brian B. and Cook, Philip and Ungar,
    Lyle and Trojanowski, John Q. and Grossman, Murray},
    title = {{T}he power of neuroimaging biomarkers for screening frontotemporal
    dementia.},
    journal = {{H}um {B}rain {M}app},
    year = {2014},
    volume = {35},
    pages = {4827--4840},
    number = {9},
    month = {Sep},
    abstract = {Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous
    neurodegenerative disease that can result from either frontotemporal
    lobar degeneration (FTLD) or Alzheimer's disease (AD) pathology.
    It is critical to establish statistically powerful biomarkers that
    can achieve substantial cost-savings and increase the feasibility
    of clinical trials. We assessed three broad categories of neuroimaging
    methods to screen underlying FTLD and AD pathology in a clinical
    FTD series: global measures (e.g., ventricular volume), anatomical
    volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas,
    and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD
    patients (N = 93) with cerebrospinal fluid, gray matter (GM) magnetic
    resonance imaging (MRI), and diffusion tensor imaging (DTI) to assess
    whether they had underlying FTLD or AD pathology. Linear regression
    was performed to identify the optimal VOIs for each method in a training
    dataset and then we evaluated classification sensitivity and specificity
    in an independent test cohort. Power was evaluated by calculating
    minimum sample sizes required in the test classification analyses
    for each model. The data-driven VOI analysis using a multimodal combination
    of GM MRI and DTI achieved the greatest classification accuracy (89\%
    sensitive and 89\% specific) and required a lower minimum sample
    size (N = 26) relative to anatomical VOI and global measures. We
    conclude that a data-driven VOI approach using Eigenanatomy provides
    more accurate classification, benefits from increased statistical
    power in unseen datasets, and therefore provides a robust method
    for screening underlying pathology in FTD patients for entry into
    clinical trials. Hum Brain Mapp 35:4827-4840, 2014. © 2014 Wiley
    Periodicals, Inc.},
    doi = {10.1002/hbm.22515},
    institution = {{D}epartment of {N}eurology, {P}enn {F}rontotemporal {D}egeneration
    {C}enter, {U}niversity of {P}ennsylvania {P}erelman {S}chool of {M}edicine,
    {P}hiladelphia, {P}ennsylvania.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {24687814},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1002/hbm.22515}
    }
  • [DOI] C. T. McMillan, J. B. Toledo, B. B. Avants, P. A. Cook, E. M. Wood, E. Suh, D. Irwin, J. Powers, C. Olm, L. Elman, L. McCluskey, G. D. Schellenberg, V. M-Y. Lee, J. Q. Trojanowski, V. M. {Van Deerlin}, and M. Grossman, “Genetic and neuroanatomic associations in sporadic frontotemporal lobar degeneration.,” Neurobiol Aging, vol. 35, iss. 6, pp. 1473-1482, 2014.
    [Bibtex]
    @ARTICLE{McMillan2014NA,
    author = {McMillan, Corey T. and Toledo, Jon B. and Avants, Brian B. and Cook,
    Philip A. and Wood, Elisabeth M. and Suh, Eunran and Irwin, David
    J. and Powers, John and Olm, Christopher and Elman, Lauren and McCluskey,
    Leo and Schellenberg, Gerard D. and Lee, Virginia M-Y. and Trojanowski,
    John Q. and {Van Deerlin}, Vivianna M. and Grossman, Murray},
    title = {{G}enetic and neuroanatomic associations in sporadic frontotemporal
    lobar degeneration.},
    journal = {{N}eurobiol {A}ging},
    year = {2014},
    volume = {35},
    pages = {1473--1482},
    number = {6},
    month = {Jun},
    abstract = {Genome-wide association studies have identified single nucleotide
    polymorphisms (SNPs) that are sensitive for tau or TDP-43 pathology
    in frontotemporal lobar degeneration (FTLD). Neuroimaging analyses
    have revealed distinct distributions of disease in FTLD patients
    with genetic mutations. However, genetic influences on neuroanatomic
    structure in sporadic FTLD have not been assessed. In this report,
    we use novel multivariate tools, Eigenanatomy, and sparse canonical
    correlation analysis to identify associations between SNPs and neuroanatomic
    structure in sporadic FTLD. Magnetic resonance imaging analyses revealed
    that rs8070723 (MAPT) was associated with gray matter variance in
    the temporal cortex. Diffusion tensor imaging analyses revealed that
    rs1768208 (MOBP), rs646776 (near SORT1), and rs5848 (PGRN) were associated
    with white matter variance in the midbrain and superior longitudinal
    fasciculus. In an independent autopsy series, we observed that rs8070723
    and rs1768208 conferred significant risk of tau pathology relative
    to TDP-43, and rs646776 conferred increased risk of TDP-43 pathology
    relative to tau. Identified brain regions and SNPs may help provide
    an in vivo screen for underlying pathology in FTLD and contribute
    to our understanding of sporadic FTLD.},
    doi = {10.1016/j.neurobiolaging.2013.11.029},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania {P}erelman
    {S}chool of {M}edicine, {P}hiladelphia, {PA}, {USA}; {P}enn {F}rontotemporal
    {D}egeneration {C}enter, {U}niversity of {P}ennsylvania {P}erelman
    {S}chool of {M}edicine, {P}hiladelphia, {PA}, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0197-4580(13)00613-1},
    pmid = {24373676},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1016/j.neurobiolaging.2013.11.029}
    }
  • [DOI] J. E. Peelle, J. Powers, P. A. Cook, E. E. Smith, and M. Grossman, “Frontotemporal neural systems supporting semantic processing in Alzheimer’s disease.,” Cogn Affect Behav Neurosci, vol. 14, iss. 1, pp. 37-48, 2014.
    [Bibtex]
    @ARTICLE{Peelle2014CABN,
    author = {Peelle, Jonathan E. and Powers, John and Cook, Philip A. and Smith,
    Edward E. and Grossman, Murray},
    title = {{F}rontotemporal neural systems supporting semantic processing in
    {A}lzheimer's disease.},
    journal = {{C}ogn {A}ffect {B}ehav {N}eurosci},
    year = {2014},
    volume = {14},
    pages = {37--48},
    number = {1},
    month = {Mar},
    abstract = {We hypothesized that semantic memory for object concepts involves
    both representations of visual feature knowledge in modality-specific
    association cortex and heteromodal regions that are important for
    integrating and organizing this semantic knowledge so that it can
    be used in a flexible, contextually appropriate manner. We examined
    this hypothesis in an fMRI study of mild Alzheimer's disease (AD).
    Participants were presented with pairs of printed words and asked
    whether the words matched on a given visual-perceptual feature (e.g.,
    guitar, violin: SHAPE). The stimuli probed natural kinds and manufactured
    objects, and the judgments involved shape or color. We found activation
    of bilateral ventral temporal cortex and left dorsolateral prefrontal
    cortex during semantic judgments, with AD patients showing less activation
    of these regions than healthy seniors. Moreover, AD patients showed
    less ventral temporal activation than did healthy seniors for manufactured
    objects, but not for natural kinds. We also used diffusion-weighted
    MRI of white matter to examine fractional anisotropy (FA). Patients
    with AD showed significantly reduced FA in the superior longitudinal
    fasciculus and inferior frontal-occipital fasciculus, which carry
    projections linking temporal and frontal regions of this semantic
    network. Our results are consistent with the hypothesis that semantic
    memory is supported in part by a large-scale neural network involving
    modality-specific association cortex, heteromodal association cortex,
    and projections between these regions. The semantic deficit in AD
    thus arises from gray matter disease that affects the representation
    of feature knowledge and processing its content, as well as white
    matter disease that interrupts the integrated functioning of this
    large-scale network.},
    doi = {10.3758/s13415-013-0239-6},
    institution = {{P}enn {F}rontotemporal {D}egeneration {C}enter and {D}epartment
    of {N}eurology, {U}niversity of {P}ennsylvania, {P}hiladelphia, {PA},
    {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {24425352},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.3758/s13415-013-0239-6}
    }
  • [DOI] A. M. Pouch, M. Vergnat, J. R. McGarvey, G. Ferrari, B. M. Jackson, C. M. Sehgal, P. A. Yushkevich, R. C. Gorman, and J. Gorman 3rd, “Statistical assessment of normal mitral annular geometry using automated three-dimensional echocardiographic analysis.,” Ann Thorac Surg, vol. 97, iss. 1, pp. 71-77, 2014.
    [Bibtex]
    @ARTICLE{Pouch2014ATS,
    author = {Pouch, Alison M. and Vergnat, Mathieu and McGarvey, Jeremy R. and
    Ferrari, Giovanni and Jackson, Benjamin M. and Sehgal, Chandra M.
    and Yushkevich, Paul A. and Gorman, Robert C. and Gorman, 3rd, Joseph
    H},
    title = {{S}tatistical assessment of normal mitral annular geometry using
    automated three-dimensional echocardiographic analysis.},
    journal = {{A}nn {T}horac {S}urg},
    year = {2014},
    volume = {97},
    pages = {71--77},
    number = {1},
    month = {Jan},
    abstract = {The basis of mitral annuloplasty ring design has progressed from qualitative
    surgical intuition to experimental and theoretical analysis of annular
    geometry with quantitative imaging techniques. In this work, we present
    an automated three-dimensional (3D) echocardiographic image analysis
    method that can be used to statistically assess variability in normal
    mitral annular geometry to support advancement in annuloplasty ring
    design.Three-dimensional patient-specific models of the mitral annulus
    were automatically generated from 3D echocardiographic images acquired
    from subjects with normal mitral valve structure and function. Geometric annular
    measurements including annular circumference, annular height, septolateral
    diameter, intercommissural width, and the annular height to intercommissural
    width ratio were automatically calculated. A mean 3D annular contour
    was computed, and principal component analysis was used to evaluate
    variability in normal annular shape.The following mean ± standard
    deviations were obtained from 3D echocardiographic image analysis:
    annular circumference, 107.0 ± 14.6 mm; annular height, 7.6 ± 2.8
    mm; septolateral diameter, 28.5 ± 3.7 mm; intercommissural width,
    33.0 ± 5.3 mm; and annular height to intercommissural width ratio,
    22.7\% ± 6.9\%. Principal component analysis indicated that shape
    variability was primarily related to overall annular size, with more
    subtle variation in the skewness and height of the anterior annular
    peak, independent of annular diameter.Patient-specific 3D echocardiographic-based
    modeling of the human mitral valve enables statistical analysis of
    physiologically normal mitral annular geometry. The tool can potentially
    lead to the development of a new generation of annuloplasty rings
    that restore the diseased mitral valve annulus back to a truly normal
    geometry.},
    doi = {10.1016/j.athoracsur.2013.07.096},
    institution = {{G}orman {C}ardiovascular {R}esearch {G}roup, {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {P}ennsylvania; {D}epartment of {S}urgery, {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {P}ennsylvania. {E}lectronic address:
    gormanj@uphs.upenn.edu.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S0003-4975(13)01709-8},
    pmid = {24090576},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.athoracsur.2013.07.096}
    }
  • [DOI] A. M. Pouch, H. Wang, M. Takabe, B. M. Jackson, J. Gorman 3rd, R. C. Gorman, P. A. Yushkevich, and C. M. Sehgal, “Fully automatic segmentation of the mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas joint label fusion and deformable medial modeling.,” Med Image Anal, vol. 18, iss. 1, pp. 118-129, 2014.
    [Bibtex]
    @ARTICLE{Pouch2014MIA,
    author = {Pouch, A. M. and Wang, H. and Takabe, M. and Jackson, B. M. and Gorman,
    3rd, JH and Gorman, R. C. and Yushkevich, P. A. and Sehgal, C. M.},
    title = {{F}ully automatic segmentation of the mitral leaflets in 3{D} transesophageal
    echocardiographic images using multi-atlas joint label fusion and
    deformable medial modeling.},
    journal = {{M}ed {I}mage {A}nal},
    year = {2014},
    volume = {18},
    pages = {118--129},
    number = {1},
    month = {Jan},
    abstract = {Comprehensive visual and quantitative analysis of in vivo human mitral
    valve morphology is central to the diagnosis and surgical treatment
    of mitral valve disease. Real-time 3D transesophageal echocardiography
    (3D TEE) is a practical, highly informative imaging modality for
    examining the mitral valve in a clinical setting. To facilitate visual
    and quantitative 3D TEE image analysis, we describe a fully automated
    method for segmenting the mitral leaflets in 3D TEE image data. The
    algorithm integrates complementary probabilistic segmentation and
    shape modeling techniques (multi-atlas joint label fusion and deformable
    modeling with continuous medial representation) to automatically
    generate 3D geometric models of the mitral leaflets from 3D TEE image
    data. These models are unique in that they establish a shape-based
    coordinate system on the valves of different subjects and represent
    the leaflets volumetrically, as structures with locally varying thickness.
    In this work, expert image analysis is the gold standard for evaluating
    automatic segmentation. Without any user interaction, we demonstrate
    that the automatic segmentation method accurately captures patient-specific
    leaflet geometry at both systole and diastole in 3D TEE data acquired
    from a mixed population of subjects with normal valve morphology
    and mitral valve disease.},
    doi = {10.1016/j.media.2013.10.001},
    institution = {{D}epartment of {B}ioengineering, {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {PA}, {U}nited {S}tates; {G}orman {C}ardiovascular
    {R}esearch {G}roup, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA}, {U}nited {S}tates. {E}lectronic address: pouch@seas.upenn.edu.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S1361-8415(13)00142-4},
    pmid = {24184435},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.media.2013.10.001}
    }
  • [DOI] E. K. Shang, E. Lai, A. M. Pouch, R. Hinmon, R. C. Gorman, J. H. Gorman 3rd, C. Sehgal, G. Ferrari, J. E. Bavaria, and B. Jackson, “Validation of semiautomated and locally resolved aortic wall thickness measurements from computed tomography.,” J Vasc Surg, 2014.
    [Bibtex]
    @ARTICLE{Shang2014JVS,
    author = {Shang, Eric K. and Lai, Eric and Pouch, Alison M. and Hinmon, Robin
    and Gorman, Robert C. and Gorman, 3rd, Joseph H and Sehgal, Chandra
    M. and Ferrari, Giovanni and Bavaria, Joseph E. and Jackson, Benjamin
    M.},
    title = {{V}alidation of semiautomated and locally resolved aortic wall thickness
    measurements from computed tomography.},
    journal = {{J} {V}asc {S}urg},
    year = {2014},
    month = {Jan},
    abstract = {Aortic wall thickness (AWT) is important for anatomic description
    and biomechanical modeling of aneurysmal disease. However, no validated,
    noninvasive method for measuring AWT exists. We hypothesized that
    semiautomated image segmentation algorithms applied to computed tomography
    angiography (CTA) can accurately measure AWT.Aortic samples from
    10 patients undergoing open thoracoabdominal aneurysm repair were
    taken from sites of the proximal or distal anastomosis, or both,
    yielding 13 samples. Aortic specimens were fixed in formalin, embedded
    in paraffin, and sectioned. After staining with hematoxylin and eosin
    and Masson's trichrome, sections were digitally scanned and measured.
    Patients' preoperative CTA Digital Imaging and Communications in
    Medicine (DICOM; National Electrical Manufacturers Association, Rosslyn,
    Va) images were segmented into luminal, inner arterial, and outer
    arterial surfaces with custom algorithms using active contours, isoline
    contour detection, and texture analysis. AWT values derived from
    image data were compared with measurements of corresponding pathologic
    specimens.AWT determined by CTA averaged 2.33 ± 0.66 mm (range, 1.52-3.55 mm),
    and the AWT of pathologic specimens averaged 2.36 ± 0.75 mm (range,
    1.51-4.16 mm). The percentage difference between pathologic specimens
    and CTA-determined AWT was 9.5\% ± 4.1\% (range, 1.8\%-16.7\%). The
    correlation between image-based measurements and pathologic measurements
    was high (R = 0.935). The 95\% limits of agreement computed by Bland-Altman
    analysis fell within the range of -0.42 and 0.42 mm.Semiautomated
    analysis of CTA images can be used to accurately measure regional
    and patient-specific AWT, as validated using pathologic ex vivo human
    aortic specimens. Descriptions and reconstructions of aortic aneurysms
    that incorporate locally resolved wall thickness are feasible and
    may improve future attempts at biomechanical analyses.},
    doi = {10.1016/j.jvs.2013.11.065},
    institution = {{D}epartment of {S}urgery, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {P}a; {D}ivision of {V}ascular {S}urgery and {E}ndovascular {T}herapy,
    {U}niversity of {P}ennsylvania, {P}hiladelphia, {P}a. {E}lectronic
    address: benjamin.jackson@uphs.upenn.edu.},
    language = {eng},
    medline-pst = {aheadofprint},
    owner = {alison},
    pii = {S0741-5214(13)02160-5},
    pmid = {24388698},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.jvs.2013.11.065}
    }
  • [DOI] N. J. Tustison, B. B. Avants, P. A. Cook, J. Kim, J. Whyte, J. C. Gee, and J. Stone, “Logical circularity in voxel-based analysis: normalization strategy may induce statistical bias.,” Hum Brain Mapp, vol. 35, iss. 3, pp. 745-759, 2014.
    [Bibtex]
    @ARTICLE{Tustison2014HBM,
    author = {Tustison, Nicholas J. and Avants, Brian B. and Cook, Philip A. and
    Kim, Junghoon and Whyte, John and Gee, James C. and Stone, James
    R.},
    title = {{L}ogical circularity in voxel-based analysis: normalization strategy
    may induce statistical bias.},
    journal = {{H}um {B}rain {M}app},
    year = {2014},
    volume = {35},
    pages = {745--759},
    number = {3},
    month = {Mar},
    abstract = {Recent discussions within the neuroimaging community have highlighted
    the problematic presence of selection bias in experimental design.
    Although initially centering on the selection of voxels during the
    course of fMRI studies, we demonstrate how this bias can potentially
    corrupt voxel-based analyses. For such studies, template-based registration
    plays a critical role in which a representative template serves as
    the normalized space for group alignment. A standard approach maps
    each subject's image to a representative template before performing
    statistical comparisons between different groups. We analytically
    demonstrate that in these scenarios the popular sum of squared difference
    (SSD) intensity metric, implicitly surrogating as a quantification
    of anatomical alignment, instead explicitly maximizes effect size--an
    experimental design flaw referred to as "circularity bias." We illustrate
    how this selection bias varies in strength with the similarity metric
    used during registration under the hypothesis that while SSD-related
    metrics, such as Demons, will manifest similar effects, other metrics
    which are not formulated based on absolute intensity differences
    will produce less of an effect. Consequently, given the variability
    in voxel-based analysis outcomes with similarity metric choice, we
    caution researchers specifically in the use of SSD and SSD-related
    measures where normalization and statistical analysis involve the
    same image set. Instead, we advocate a more cautious approach where
    normalization of the individual subject images to the reference space
    occurs through corresponding image sets which are independent of
    statistical testing. Alternatively, one can use similarity terms
    that are less sensitive to this bias.},
    doi = {10.1002/hbm.22211},
    institution = {{D}epartment of {R}adiology and {M}edical {I}maging, {U}niversity
    of {V}irginia, {C}harlottesville, {V}irginia.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {23151955},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1002/hbm.22211}
    }
  • [DOI] N. J. Tustison, P. A. Cook, A. Klein, G. Song, S. R. Das, J. T. Duda, B. Kandel, N. {van Strien}, J. R. Stone, J. C. Gee, and B. B. Avants, “Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements.,” Neuroimage, vol. 99, pp. 166-179, 2014.
    [Bibtex]
    @ARTICLE{Tustison2014N,
    author = {Tustison, Nicholas J. and Cook, Philip A. and Klein, Arno and Song,
    Gang and Das, Sandhitsu R. and Duda, Jeffrey T. and Kandel, Benjamin
    M. and {van Strien}, Niels and Stone, James R. and Gee, James C.
    and Avants, Brian B.},
    title = {{L}arge-scale evaluation of {ANT}s and {F}ree{S}urfer cortical thickness
    measurements.},
    journal = {{N}euroimage},
    year = {2014},
    volume = {99},
    pages = {166--179},
    month = {Oct},
    abstract = {Many studies of the human brain have explored the relationship between
    cortical thickness and cognition, phenotype, or disease. Due to the
    subjectivity and time requirements in manual measurement of cortical
    thickness, scientists have relied on robust software tools for automation
    which facilitate the testing and refinement of neuroscientific hypotheses.
    The most widely used tool for cortical thickness studies is the publicly
    available, surface-based FreeSurfer package. Critical to the adoption
    of such tools is a demonstration of their reproducibility, validity,
    and the documentation of specific implementations that are robust
    across large, diverse imaging datasets. To this end, we have developed
    the automated, volume-based Advanced Normalization Tools (ANTs) cortical
    thickness pipeline comprising well-vetted components such as SyGN
    (multivariate template construction), SyN (image registration), N4
    (bias correction), Atropos (n-tissue segmentation), and DiReCT (cortical
    thickness estimation). In this work, we have conducted the largest
    evaluation of automated cortical thickness measures in publicly available
    data, comparing FreeSurfer and ANTs measures computed on 1205 images
    from four open data sets (IXI, MMRR, NKI, and OASIS), with parcellation
    based on the recently proposed Desikan-Killiany-Tourville (DKT) cortical
    labeling protocol. We found good scan-rescan repeatability with both
    FreeSurfer and ANTs measures. Given that such assessments of precision
    do not necessarily reflect accuracy or an ability to make statistical
    inferences, we further tested the neurobiological validity of these
    approaches by evaluating thickness-based prediction of age and gender.
    ANTs is shown to have a higher predictive performance than FreeSurfer
    for both of these measures. In promotion of open science, we make
    all of our scripts, data, and results publicly available which complements
    the use of open image data sets and the open source availability
    of the proposed ANTs cortical thickness pipeline.},
    doi = {10.1016/j.neuroimage.2014.05.044},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {PA}, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S1053-8119(14)00409-1},
    pmid = {24879923},
    timestamp = {2014.10.31},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2014.05.044}
    }
  • J. Wu, M. Ashtari, L. M. Betancourt, N. L. Brodsky, J. Giannetta, J. Gee, H. Hurt, and B. Avants, “Cortical Parcellation for Neonatal Brains in MRI,” in Proc. 2014 Pediatric Academic Societies, Vancouver, Canada, 2014.
    [Bibtex]
    @CONFERENCE{WuPAS2014a,
    author = {Jue Wu and Manzar Ashtari and Laura M. Betancourt and Nancy L. Brodsky
    and Joan Giannetta and James Gee and Hallam Hurt and Brian Avants},
    title = {{C}ortical {P}arcellation for {N}eonatal {B}rains in {MRI}},
    booktitle = {{P}roc. 2014 {P}ediatric {A}cademic {S}ocieties, {V}ancouver, {C}anada},
    year = {2014},
    owner = {johnwoo},
    timestamp = {2014.02.12}
    }
  • J. Wu, P. Schwab, A. Vossough, J. Gee, and Daniel Licht, “Brain Templates for Neonates with Congenital Heart Defects: Preliminary Results from an International Consortium,” in Proc. Joint Annual Meeting ISMRM-ESMRMB, Milan, Italy, 2014, p. abstract no. 5019.
    [Bibtex]
    @CONFERENCE{WuISMRM2014,
    author = {Jue Wu and Peter Schwab and Arastoo Vossough and James Gee and Daniel
    Licht},
    title = {{B}rain {T}emplates for {N}eonates with {C}ongenital {H}eart {D}efects:
    {P}reliminary {R}esults from an {I}nternational {C}onsortium},
    booktitle = {{P}roc. {J}oint {A}nnual {M}eeting {ISMRM}-{ESMRMB}, {M}ilan, {I}taly},
    year = {2014},
    pages = {abstract no. 5019},
    owner = {johnwoo},
    timestamp = {2014.02.12}
    }
  • J. Wu, P. Schwab, A. Vossough, J. Gee, and Daniel Licht, “Brain Templates for Neonates With Congenital Heart Defects: Preliminary Results from an International Consortium,” in Proc. 2014 Pediatric Academic Societies, Vancouver, Canada, 2014.
    [Bibtex]
    @CONFERENCE{WuPAS2014b,
    author = {Jue Wu and Peter Schwab and Arastoo Vossough and James Gee and Daniel
    Licht},
    title = {{B}rain {T}emplates for {N}eonates {W}ith {C}ongenital {H}eart {D}efects:
    {P}reliminary {R}esults from an {I}nternational {C}onsortium},
    booktitle = {{P}roc. 2014 {P}ediatric {A}cademic {S}ocieties, {V}ancouver, {C}anada},
    year = {2014},
    owner = {johnwoo},
    timestamp = {2014.02.12}
    }

2013

  • D. H. Adler, S. Chan, and J. R. Mitchell, “Affine Medical Image Registration Using the Graphics Processing Unit.” CRC Press, 2013, pp. 223-246.
    [Bibtex]
    @INBOOK{Adler2013IPRT,
    chapter = {16 of Image Processing in Radiation Therapy},
    pages = {223--246},
    title = {{A}ffine {M}edical {I}mage {R}egistration {U}sing the {G}raphics
    {P}rocessing {U}nit},
    publisher = {CRC Press},
    year = {2013},
    author = {Adler, D. H. and Chan, S. and Mitchell, J. R.}
    }
  • M. Ashtari, L. Cyckowski, G. Zhang, P. Cook, K. Marshall, J. Wellman, J. Gee, A. Vossough, K. Shindler, A. Maguire, and J. Bennett, “Retinal Gene Therapy May Alter Connectivity of Visual Pathways,” in MOLECULAR THERAPY, 2013, p. S22–S22.
    [Bibtex]
    @INPROCEEDINGS{ashtari2013retinal,
    author = {Ashtari, M and Cyckowski, L and Zhang, G and Cook, P and Marshall,
    K and Wellman, J and Gee, J and Vossough, A and Shindler, K and Maguire,
    A and Bennett, J},
    title = {{R}etinal {G}ene {T}herapy {M}ay {A}lter {C}onnectivity of {V}isual
    {P}athways},
    booktitle = {{MOLECULAR} {THERAPY}},
    year = {2013},
    volume = {21},
    pages = {S22--S22},
    organization = {NATURE PUBLISHING GROUP 75 VARICK ST, 9TH FLR, NEW YORK, NY 10013-1917
    USA},
    owner = {pcook},
    timestamp = {2013.10.22}
    }
  • [DOI] D. A. Bangasser, C. S. Lee, P. A. Cook, J. C. Gee, S. Bhatnagar, and R. J. Valentino, “Manganese-enhanced magnetic resonance imaging (MEMRI) reveals brain circuitry involved in responding to an acute novel stress in rats with a history of repeated social stress.,” Physiol Behav, vol. 122, pp. 228-236, 2013.
    [Bibtex]
    @ARTICLE{Bangasser2013PB,
    author = {Bangasser, Debra A. and Lee, Catherine S. and Cook, Philip A. and
    Gee, James C. and Bhatnagar, Seema and Valentino, Rita J.},
    title = {{M}anganese-enhanced magnetic resonance imaging ({MEMRI}) reveals
    brain circuitry involved in responding to an acute novel stress in
    rats with a history of repeated social stress.},
    journal = {{P}hysiol {B}ehav},
    year = {2013},
    volume = {122},
    pages = {228--236},
    month = {Oct},
    abstract = {Responses to acute stressors are determined in part by stress history.
    For example, a history of chronic stress results in facilitated responses
    to a novel stressor and this facilitation is considered to be adaptive.
    We previously demonstrated that repeated exposure of rats to the
    resident-intruder model of social stress results in the emergence
    of two subpopulations that are characterized by different coping
    responses to stress. The submissive subpopulation failed to show
    facilitation to a novel stressor and developed a passive strategy
    in the Porsolt forced swim test. Because a passive stress coping
    response has been implicated in the propensity to develop certain
    psychiatric disorders, understanding the unique circuitry engaged
    by exposure to a novel stressor in these subpopulations would advance
    our understanding of the etiology of stress-related pathology. An
    ex vivo functional imaging technique, manganese-enhanced magnetic
    resonance imaging (MEMRI), was used to identify and distinguish brain
    regions that are differentially activated by an acute swim stress
    (15 min) in rats with a history of social stress compared to controls.
    Specifically, Mn(2+) was administered intracerebroventricularly prior
    to swim stress and brains were later imaged ex vivo to reveal activated
    structures. When compared to controls, all rats with a history of
    social stress showed greater activation in specific striatal, hippocampal,
    hypothalamic, and midbrain regions. The submissive subpopulation
    of rats was further distinguished by significantly greater activation
    in amygdala, bed nucleus of the stria terminalis, and septum, suggesting
    that these regions may form a circuit mediating responses to novel
    stress in individuals that adopt passive coping strategies. The finding
    that different circuits are engaged by a novel stressor in the two
    subpopulations of rats exposed to social stress implicates a role
    for these circuits in determining individual strategies for responding
    to stressors. Finally, these data underscore the utility of ex vivo
    MEMRI to identify and distinguish circuits engaged in behavioral
    responses.},
    doi = {10.1016/j.physbeh.2013.04.008},
    institution = {{D}epartment of {A}nesthesiology and {C}ritical {C}are {M}edicine,
    {C}hildren's {H}ospital of {P}hiladelphia, {P}hiladelphia, {PA} 19104,
    {U}nited {S}tates; {D}epartment of {P}sychology and {N}euroscience
    {P}rogram, {T}emple {U}niversity, {P}hiladelphia, {PA} 19122, {U}nited
    {S}tates. {E}lectronic address: debra.bangasser@temple.edu.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0031-9384(13)00122-4},
    pmid = {23643825},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1016/j.physbeh.2013.04.008}
    }
  • [DOI] M. F. Bonner, J. E. Peelle, P. A. Cook, and M. Grossman, “Heteromodal conceptual processing in the angular gyrus.,” Neuroimage, vol. 71C, pp. 175-186, 2013.
    [Bibtex]
    @ARTICLE{Bonner2013N,
    author = {Bonner, Michael F. and Peelle, Jonathan E. and Cook, Philip A. and
    Grossman, Murray},
    title = {{H}eteromodal conceptual processing in the angular gyrus.},
    journal = {{N}euroimage},
    year = {2013},
    volume = {71C},
    pages = {175--186},
    month = {Jan},
    abstract = {Concepts bind together the features commonly associated with objects
    and events to form networks in long-term semantic memory. These conceptual
    networks are the basis of human knowledge and underlie perception,
    imagination, and the ability to communicate about experiences and
    the contents of the environment. Although it is often assumed that
    this distributed semantic information is integrated in higher-level
    heteromodal association cortices, open questions remain about the
    role and anatomic basis of heteromodal representations in semantic
    memory. Here we used combined neuroimaging evidence from functional
    magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI)
    to characterize the cortical networks underlying concept representation.
    Using a lexical decision task, we examined the processing of concepts
    in four semantic categories that varied on their sensory-motor feature
    associations (sight, sound, manipulation, and abstract). We found
    that the angular gyrus was activated across all categories regardless
    of their modality-specific feature associations, consistent with
    a heteromodal account for the angular gyrus. Exploratory analyses
    suggested that categories with weighted sensory-motor features additionally
    recruited modality-specific association cortices. Furthermore, DTI
    tractography identified white matter tracts connecting these regions
    of modality-specific functional activation with the angular gyrus.
    These findings are consistent with a distributed semantic network
    that includes a heteromodal, integrative component in the angular
    gyrus in combination with sensory-motor feature representations in
    modality-specific association cortices.},
    doi = {10.1016/j.neuroimage.2013.01.006},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA} 19104, {USA}. {E}lectronic address: michafra@upenn.mail.med.edu.},
    language = {eng},
    medline-pst = {aheadofprint},
    owner = {pcook},
    pii = {S1053-8119(13)00037-2},
    pmid = {23333416},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2013.01.006}
    }
  • P. A. Cook, B. B. Avants, C. T. McMillan, J. Powers, J. E. Peelle, J. C. Gee, and M. Grossman, “Multimodal Neuroimaging Reveals Gray and White Matter Associations with Language Deficits in Frontotemporal Degeneration,” in Proceedings 21st Scientific Meeting, International Society for Magnetic Resonance in Medicine, Salt Lake City, 2013, p. 1011.
    [Bibtex]
    @INPROCEEDINGS{Cook2013ISMRM,
    author = {Cook, Philip A. and Avants, B. B. and McMillan, Corey T. and Powers,
    John and Peelle, Jonathan E. and Gee, James C. and Grossman, Murray},
    title = {{M}ultimodal {N}euroimaging {R}eveals {G}ray and {W}hite {M}atter
    {A}ssociations with {L}anguage {D}eficits in {F}rontotemporal {D}egeneration},
    booktitle = {{P}roceedings 21st {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}alt {L}ake {C}ity},
    year = {2013},
    pages = {1011},
    abstract = {Language deficits are widely reported in frontotemporal dementia (FTD),
    including non-fluent primary progressive aphasia (naPPA), semantic-variant
    primary progressive aphasia (svPPA) behavioral variant FTD (bvFTD).
    We hypothesize that these deficits are due to disruption of a large-scale
    neural network involving both language and executive resources. Here
    we use multi-modal MRI and sparse statistical methods to evaluate
    whether imaging of white matter (WM) with diffusion MRI enhances
    prediction of the neuroanatomic basis for their deficit when combined
    with cortical thickness derived from T1 MRI.},
    keywords = {SLC1011}
    }
  • [DOI] S. R. Das, J. Pluta, L. Mancuso, D. Kliot, S. Orozco, B. C. Dickerson, P. A. Yushkevich, and D. A. Wolk, “Increased functional connectivity within medial temporal lobe in mild cognitive impairment.,” Hippocampus, vol. 23, iss. 1, pp. 1-6, 2013.
    [Bibtex]
    @ARTICLE{Das2013H,
    author = {Das, Sandhitsu R. and Pluta, John and Mancuso, Lauren and Kliot,
    Dasha and Orozco, Sylvia and Dickerson, Bradford C. and Yushkevich,
    Paul A. and Wolk, David A.},
    title = {{I}ncreased functional connectivity within medial temporal lobe in
    mild cognitive impairment.},
    journal = {{H}ippocampus},
    year = {2013},
    volume = {23},
    pages = {1-6},
    number = {1},
    month = {1},
    abstract = {Pathology at preclinical and prodromal stages of Alzheimer's disease
    (AD) may manifest itself as measurable functional change in neuronal
    networks earlier than detectable structural change. Functional connectivity
    as measured using resting-state functional magnetic resonance imaging
    has emerged as a useful tool for studying disease effects on baseline
    states of neuronal networks. In this study, we use high resolution
    MRI to label subregions within the medial temporal lobe (MTL), a
    site of early pathology in AD, and report an increase in functional
    connectivity in amnestic mild cognitive impairment between entorhinal
    cortex and subregions of the MTL, with the strongest effect in the
    anterior hippocampus. However, our data also replicated the effects
    of decreased connectivity of the MTL to other nodes of the default
    mode network reported by other researchers. This dissociation of
    changes in functional connectivity within the MTL versus the MTL's
    connection with other neocortical structures can help enrich the
    characterization of early stages of disease progression in AD},
    address = {United States},
    citation_identifier = {Das 2013},
    doi = {10.1002/hipo.22051},
    endnote_reference_number = {157},
    issn = {1098-1063},
    keywords = {Disease Progression;Humans;Middle Aged;Neural Pathways;Female;Entorhinal
    Cortex;Hippocampus;Cohort Studies;Male;Aged;Magnetic Resonance Imaging;Aged,
    80 and over;Temporal Lobe;research support, n.i.h., extramural;Mild
    Cognitive Impairment},
    mid = {NIHMS452636},
    organization = {Penn Image Computing and Science Laboratory (PICSL), Department of
    Radiology, University of Pennsylvania, Philadelphia, Pennsylvania,
    USA. sudas\@seas.upenn.edu},
    owner = {srdas},
    pmcid = {PMC3642853},
    pubmedid = {22815064},
    timestamp = {2014.02.19},
    us_nlm_id = {9108167},
    uuid = {17492B62-593F-41CB-A94C-DE69BB0F2D7B},
    web_data_source = {PubMed}
    }
  • [DOI] P. Dhillon, J. C. Gee, L. Ungar, and B. Avants, “Anatomically-Constrained PCA for Image Parcellation,” in Pattern Recognition in Neuroimaging (PRNI), 2013 International Workshop on, 2013, pp. 25-28.
    [Bibtex]
    @INPROCEEDINGS{Dhillon2013PRNI,
    author = {Dhillon, Paramveer and Gee, James C and Ungar, Lyle and Avants, Brian},
    title = {{A}natomically-{C}onstrained {PCA} for {I}mage {P}arcellation},
    booktitle = {{P}attern {R}ecognition in {N}euroimaging {(PRNI)}, 2013 {I}nternational
    {W}orkshop on},
    year = {2013},
    pages = {25--28},
    doi = {10.1109/PRNI.2013.16},
    owner = {paramveerdhillon},
    timestamp = {2014.02.14},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6603548}
    }
  • J. T. Duda, J. A. Detre, J. Kim, J. Gee, and B. B. Avants, “Fusing Functional Signals by Sparse Canonical Correlation Analysis Improves Network Reproducibility,” in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013, Springer, 2013, pp. 635-642.
    [Bibtex]
    @INCOLLECTION{Duda2013,
    author = {Duda, Jeffrey T and Detre, John A and Kim, Junghoon and Gee, James
    C and Avants, Brian B},
    title = {{F}using {F}unctional {S}ignals by {S}parse {C}anonical {C}orrelation
    {A}nalysis {I}mproves {N}etwork {R}eproducibility},
    booktitle = {{M}edical {I}mage {C}omputing and {C}omputer-{A}ssisted {I}ntervention--{MICCAI}
    2013},
    publisher = {Springer},
    year = {2013},
    pages = {635--642},
    owner = {jtduda},
    timestamp = {2013.11.13},
    url = {http://link.springer.com/chapter/10.1007/978-3-642-40760-4_79}
    }
  • J. T. Duda, E. Kilroy, J. C. Gee, D. Wang, and B. B. Avants, “Examining the relationship between cerebral blood flow and grey matter structure in typically developing children,” in Proceedings 21th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Salt Lake City, 2013, p. 6702.
    [Bibtex]
    @INPROCEEDINGS{Duda2013ISMRM,
    author = {Duda, Jeffrey T. and Kilroy, Emily and Gee, James C. and Wang, Danny
    and Avants, Brian B.},
    title = {{E}xamining the relationship between cerebral blood flow and grey
    matter structure in typically developing children},
    booktitle = {{P}roceedings 21th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}alt {L}ake {C}ity},
    year = {2013},
    pages = {6702},
    keywords = {SaltLakeCity6702}
    }
  • [DOI] R. G. Gross, E. Camp, C. T. McMillan, M. Dreyfuss, D. Gunawardena, P. A. Cook, B. Morgan, A. Siderowf, H. I. Hurtig, M. B. Stern, and M. Grossman, “Impairment of script comprehension in Lewy body spectrum disorders.,” Brain Lang, vol. 125, iss. 3, pp. 330-343, 2013.
    [Bibtex]
    @ARTICLE{Gross2013BL,
    author = {Gross, Rachel G. and Camp, Emily and McMillan, Corey T. and Dreyfuss,
    Michael and Gunawardena, Delani and Cook, Philip A. and Morgan, Brianna
    and Siderowf, Andrew and Hurtig, Howard I. and Stern, Matthew B.
    and Grossman, Murray},
    title = {{I}mpairment of script comprehension in {L}ewy body spectrum disorders.},
    journal = {{B}rain {L}ang},
    year = {2013},
    volume = {125},
    pages = {330--343},
    number = {3},
    month = {Jun},
    abstract = {A disabling impairment of higher-order language function can be seen
    in patients with Lewy body spectrum disorders such as Parkinson's
    disease (PD), Parkinson's disease dementia (PDD), and dementia with
    Lewy bodies (DLB). We focus on script comprehension in patients with
    Lewy body spectrum disorders. While scripts unfold sequentially,
    constituent events are thought to contain an internal organization.
    Executive dysfunction in patients with Lewy body spectrum disorders
    may interfere with comprehension of this internal structure. We examined
    42 patients (30 non-demented PD and 12 mildly demented PDD/DLB patients)
    and 12 healthy seniors. We presented 22 scripts (e.g., "going fishing"),
    each consisting of six events. Pilot data from young controls provided
    the basis for organizing associated events into clusters and arranging
    them hierarchically into scripts. We measured accuracy and latency
    to judge the order of adjacent events in the same cluster versus
    adjacent events in different clusters. PDD/DLB patients were less
    accurate in their ordering judgments than PD patients and controls.
    Healthy seniors and PD patients were significantly faster to judge
    correctly the order of highly associated within-cluster event pairs
    relative to less closely associated different-cluster event pairs,
    while PDD/DLB patients did not consistently distinguish between these
    event-pair types. This relative insensitivity to the clustered-hierarchical
    organization of events was related to executive impairment and to
    frontal atrophy as measured by volumetric MRI. These findings extend
    prior work on script processing to patients with Lewy body spectrum
    disorders and highlight the potential impact of frontal/executive
    dysfunction on the daily lives of affected patients.},
    doi = {10.1016/j.bandl.2013.02.006},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania {S}chool
    of {M}edicine, {P}hiladelphia, {PA} 19104, {USA}. rachel.goldmann@uphs.upenn.edu},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0093-934X(13)00049-7},
    pmid = {23566691},
    timestamp = {2013.08.26},
    url = {http://dx.doi.org/10.1016/j.bandl.2013.02.006}
    }
  • [DOI] M. Grossman, J. E. Peelle, E. E. Smith, C. T. McMillan, P. Cook, J. Powers, M. Dreyfuss, M. F. Bonner, L. Richmond, A. Boller, E. Camp, and L. Burkholder, “Category-specific semantic memory: converging evidence from bold fMRI and Alzheimer’s disease.,” Neuroimage, vol. 68, pp. 263-274, 2013.
    [Bibtex]
    @ARTICLE{Grossman2013N,
    author = {Grossman, Murray and Peelle, Jonathan E. and Smith, Edward E. and
    McMillan, Corey T. and Cook, Philip and Powers, John and Dreyfuss,
    Michael and Bonner, Michael F. and Richmond, Lauren and Boller, Ashley
    and Camp, Emily and Burkholder, Lisa},
    title = {{C}ategory-specific semantic memory: converging evidence from bold
    f{MRI} and {A}lzheimer's disease.},
    journal = {{N}euroimage},
    year = {2013},
    volume = {68},
    pages = {263--274},
    month = {Mar},
    abstract = {Patients with Alzheimer's disease have category-specific semantic
    memory difficulty for natural relative to manufactured objects. We
    assessed the basis for this deficit by asking healthy adults and
    patients to judge whether pairs of words share a feature (e.g. "banana:lemon-COLOR").
    In an fMRI study, healthy adults showed gray matter (GM) activation
    of temporal-occipital cortex (TOC) where visual-perceptual features
    may be represented, and prefrontal cortex (PFC) which may contribute
    to feature selection. Tractography revealed dorsal and ventral stream
    white matter (WM) projections between PFC and TOC. Patients had greater
    difficulty with natural than manufactured objects. This was associated
    with greater overlap between diseased GM areas correlated with natural
    kinds in patients and fMRI activation in healthy adults for natural
    kinds. The dorsal WM projection between PFC and TOC in patients correlated
    only with judgments of natural kinds. Patients thus remained dependent
    on the same neural network as controls during judgments of natural
    kinds, despite disease in these areas. For manufactured objects,
    patients' judgments showed limited correlations with PFC and TOC
    GM areas activated by controls, and did not correlate with the PFC-TOC
    dorsal WM tract. Regions outside of the PFC-TOC network thus may
    help support patients' judgments of manufactured objects. We conclude
    that a large-scale neural network for semantic memory implicates
    both feature knowledge representations in modality-specific association
    cortex and heteromodal regions important for accessing this knowledge,
    and that patients' relative deficit for natural kinds is due in part
    to their dependence on this network despite disease in these areas.},
    doi = {10.1016/j.neuroimage.2012.11.057},
    institution = {{F}rontotemporal {D}egeneration {C}enter, {D}epartment of {N}eurology,
    {P}erelman {S}chool of {M}edicine, {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {PA} 19104-4283, {USA}. mgrossma@mail.med.upenn.edu},
    keywords = {Adolescent; Adult; Aged; Aged, 80 and over; Alzheimer Disease, physiopathology;
    Brain Mapping; Brain, physiopathology; Diffusion Tensor Imaging;
    Female; Humans; Image Interpretation, Computer-Assisted; Male; Memory,
    physiology; Semantics; Young Adult},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S1053-8119(12)01169-X},
    pmid = {23220494},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2012.11.057}
    }
  • [DOI] D. J. Irwin, C. T. McMillan, J. Brettschneider, D. J. Libon, J. Powers, K. Rascovsky, J. B. Toledo, A. Boller, J. Bekisz, K. Chandrasekaran, E. M. Wood, L. M. Shaw, J. H. Woo, P. A. Cook, D. A. Wolk, S. Arnold, V. M. {Van Deerlin}, L. F. McCluskey, L. Elman, V. M-Y. Lee, J. Q. Trojanowski, and M. Grossman, “Cognitive decline and reduced survival in C9orf72 expansion frontotemporal degeneration and amyotrophic lateral sclerosis.,” J Neurol Neurosurg Psychiatry, vol. 84, iss. 2, pp. 163-169, 2013.
    [Bibtex]
    @ARTICLE{Irwin2013JNNP,
    author = {Irwin, David J. and McMillan, Corey T. and Brettschneider, Johannes
    and Libon, David J. and Powers, John and Rascovsky, Katya and Toledo,
    Jon B. and Boller, Ashley and Bekisz, Jonathan and Chandrasekaran,
    Keerthi and Wood, Elisabeth McCarty and Shaw, Leslie M. and Woo,
    John H. and Cook, Philip A. and Wolk, David A. and Arnold, Steven
    E. and {Van Deerlin}, Vivianna M. and McCluskey, Leo F. and Elman,
    Lauren and Lee, Virginia M-Y. and Trojanowski, John Q. and Grossman,
    Murray},
    title = {{C}ognitive decline and reduced survival in {C}9orf72 expansion frontotemporal
    degeneration and amyotrophic lateral sclerosis.},
    journal = {{J} {N}eurol {N}eurosurg {P}sychiatry},
    year = {2013},
    volume = {84},
    pages = {163--169},
    number = {2},
    month = {Feb},
    abstract = {Significant heterogeneity in clinical features of frontotemporal lobar
    degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) cases
    with the pathogenic C9orf72 expansion (C9P) have been described.
    To clarify this issue, we compared a large C9P cohort with carefully
    matched non-expansion (C9N) cases with a known or highly-suspected
    underlying TAR DNA-binding protein 43 (TDP-43) proteinopathy.A retrospective
    case-control study was carried out using available cross-sectional
    and longitudinal clinical and neuropsychological data, MRI voxel-based
    morphometry (VBM) and neuropathological assessment from 64 C9P cases
    (ALS=31, FTLD=33) and 79 C9N cases (ALS=36, FTLD=43).C9P cases had
    an earlier age of onset (p=0.047) and, in the subset of patients
    who were deceased, an earlier age of death (p=0.014) than C9N. C9P
    had more rapid progression than C9N: C9P ALS cases had a shortened
    survival (2.6±0.3 years) compared to C9N ALS (3.8±0.4 years; log-rank
    λ2=4.183, p=0.041), and C9P FTLD showed a significantly greater annualised
    rate of decline in letter fluency (4.5±1.3 words/year) than C9N FTLD
    (1.4±0.8 words/year, p=0.023). VBM revealed greater atrophy in the
    right frontoinsular, thalamus, cerebellum and bilateral parietal
    regions for C9P FTLD relative to C9N FTLD, and regression analysis
    related verbal fluency scores to atrophy in frontal and parietal
    regions. Neuropathological analysis found greater neuronal loss in
    the mid-frontal cortex in C9P FTLD, and mid-frontal cortex TDP-43
    inclusion severity correlated with poor letter fluency performance.C9P
    cases may have a shorter survival in ALS and more rapid rate of cognitive
    decline related to frontal and parietal disease in FTLD. C9orf72
    genotyping may provide useful prognostic and diagnostic clinical
    information for patients with ALS and FTLD.},
    doi = {10.1136/jnnp-2012-303507},
    institution = {{D}epartment of {N}eurology {P}erelman {S}chool of {M}edicine at
    the {U}niversity of {P}ennsylvania {H}ospital of the {U}niversity
    of {P}ennsylvania 3400 {S}pruce {S}treet, {P}hiladelphia, {PA} 19104,
    {USA}; mgrossma@mail.med.upenn.edu.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {jnnp-2012-303507},
    pmid = {23117491},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1136/jnnp-2012-303507}
    }
  • B. M. Kandel, D. A. Wolk, J. C. Gee, and B. Avants, “Predicting cognitive data from medical images using sparse linear regression,” in Information Processing in Medical Imaging, Springer Berlin Heidelberg, 2013, pp. 86-97.
    [Bibtex]
    @INCOLLECTION{Kandel2013,
    author = {Kandel, Benjamin M and Wolk, David A and Gee, James C and Avants,
    Brian},
    title = {{P}redicting cognitive data from medical images using sparse linear
    regression},
    booktitle = {{I}nformation {P}rocessing in {M}edical {I}maging},
    publisher = {Springer Berlin Heidelberg},
    year = {2013},
    pages = {86--97},
    owner = {ben},
    timestamp = {2014.03.28}
    }
  • M. Kumar, J. T. Duda, R. Ittyerah, D. Adler, S. Pickup, E. S. Brodkin, T. Abel, J. C. Gee, and H. Poptani, “High resolution diffusion tensor imaging to assess brain microstructural abnormalities in a Neuroligin-3 knockin mouse model associated with Autism spectrum disorders,” in Proceedings 21st Scientific Meeting, International Society for Magnetic Resonance in Medicine, Salt Lake City, 2013, p. 1046.
    [Bibtex]
    @INPROCEEDINGS{Kumar2013ISMRM,
    author = {Kumar, M. and Duda, J. T. and Ittyerah, R. and Adler, D. and Pickup,
    S. and Brodkin, E. S. and Abel, T. and Gee, J. C. and Poptani, H.},
    title = {{H}igh resolution diffusion tensor imaging to assess brain microstructural
    abnormalities in a {Neuroligin-3} knockin mouse model associated
    with {A}utism spectrum disorders},
    booktitle = {{P}roceedings 21st {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}alt {L}ake {C}ity},
    year = {2013},
    pages = {1046}
    }
  • G. M. Lawson, J. T. Duda, B. B. Avants, J. Wu, and M. J. Farah, “Associations between children’s socioeconomic status and prefrontal cortical thickness,” Developmental Science, 2013.
    [Bibtex]
    @ARTICLE{Lawson2013,
    author = {Lawson, Gwendolyn M and Duda, Jeffrey T and Avants, Brian B and Wu,
    Jue and Farah, Martha J},
    title = {{A}ssociations between children's socioeconomic status and prefrontal
    cortical thickness},
    journal = {{D}evelopmental {S}cience},
    year = {2013},
    owner = {jtduda},
    publisher = {Wiley Online Library},
    timestamp = {2013.08.09},
    url = {http://onlinelibrary.wiley.com/doi/10.1111/desc.12096/full}
    }
  • [DOI] C. T. McMillan, D. J. Irwin, B. B. Avants, J. Powers, P. A. Cook, J. B. Toledo, E. {McCarty Wood}, V. M. {Van Deerlin}, V. M-Y. Lee, J. Q. Trojanowski, and M. Grossman, “White matter imaging helps dissociate tau from TDP-43 in frontotemporal lobar degeneration.,” J Neurol Neurosurg Psychiatry, vol. 84, iss. 9, pp. 949-955, 2013.
    [Bibtex]
    @ARTICLE{McMillan2013JNNP,
    author = {McMillan, Corey T. and Irwin, David J. and Avants, Brian B. and Powers,
    John and Cook, Philip A. and Toledo, Jon B. and {McCarty Wood}, Elisabeth
    and {Van Deerlin}, Vivianna M. and Lee, Virginia M-Y. and Trojanowski,
    John Q. and Grossman, Murray},
    title = {{W}hite matter imaging helps dissociate tau from {TDP}-43 in frontotemporal
    lobar degeneration.},
    journal = {{J} {N}eurol {N}eurosurg {P}sychiatry},
    year = {2013},
    volume = {84},
    pages = {949--955},
    number = {9},
    month = {Sep},
    abstract = {Frontotemporal lobar degeneration (FTLD) is most commonly associated
    with TAR-DNA binding protein (TDP-43) or tau pathology at autopsy,
    but there are no in vivo biomarkers reliably discriminating between
    sporadic cases. As disease-modifying treatments emerge, it is critical
    to accurately identify underlying pathology in living patients so
    that they can be entered into appropriate etiology-directed clinical
    trials. Patients with tau inclusions (FTLD-TAU) appear to have relatively
    greater white matter (WM) disease at autopsy than those patients
    with TDP-43 (FTLD-TDP). In this paper, we investigate the ability
    of white matter (WM) imaging to help discriminate between FTLD-TAU
    and FTLD-TDP during life using diffusion tensor imaging (DTI).Patients
    with autopsy-confirmed disease or a genetic mutation consistent with
    FTLD-TDP or FTLD-TAU underwent multimodal T1 volumetric MRI and diffusion
    weighted imaging scans. We quantified cortical thickness in GM and
    fractional anisotropy (FA) in WM. We performed Eigenanatomy, a statistically
    robust dimensionality reduction algorithm, and used leave-one-out
    cross-validation to predict underlying pathology. Neuropathological
    assessment of GM and WM disease burden was performed in the autopsy-cases
    to confirm our findings of an ante-mortem GM and WM dissociation
    in the neuroimaging cohort.ROC curve analyses evaluated classification
    accuracy in individual patients and revealed 96\% sensitivity and
    100\% specificity for WM analyses. FTLD-TAU had significantly more
    WM degeneration and inclusion severity at autopsy relative to FTLD-TDP.These
    neuroimaging and neuropathological investigations provide converging
    evidence for greater WM burden associated with FTLD-TAU, and emphasise
    the role of WM neuroimaging for in vivo discrimination between FTLD-TAU
    and FTLD-TDP.},
    doi = {10.1136/jnnp-2012-304418},
    institution = {{D}epartment of {N}eurology, {P}erelman {S}chool of {M}edicine, {F}rontotemporal
    {D}egeneration {C}enter, {U}niversity of {P}ennsylvania, , {P}hiladelphia,
    {P}ennsylvania, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {jnnp-2012-304418},
    pmid = {23475817},
    timestamp = {2013.08.26},
    url = {http://dx.doi.org/10.1136/jnnp-2012-304418}
    }
  • A. M. Pouch, H. Wang, M. Takabe, B. M. Jackson, C. M. Sehgal, J. H. Gorman 3rd, R. C. Gorman, and P. A. Yushkevich, “Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.,” Med Image Comput Comput Assist Interv, vol. 16, iss. Pt 1, pp. 485-492, 2013.
    [Bibtex]
    @ARTICLE{Pouch2013MICCAI,
    author = {Pouch, Alison M. and Wang, Hongzhi and Takabe, Manabu and Jackson,
    Benjamin M. and Sehgal, Chandra M. and Gorman, 3rd, Joseph H and
    Gorman, Robert C. and Yushkevich, Paul A.},
    title = {{A}utomated segmentation and geometrical modeling of the tricuspid
    aortic valve in 3{D} echocardiographic images.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2013},
    volume = {16},
    pages = {485--492},
    number = {Pt 1},
    abstract = {The aortic valve has been described with variable anatomical definitions,
    and the consistency of 2D manual measurement of valve dimensions
    in medical image data has been questionable. Given the importance
    of image-based morphological assessment in the diagnosis and surgical
    treatment of aortic valve disease, there is considerable need to
    develop a standardized framework for 3D valve segmentation and shape
    representation. Towards this goal, this work integrates template-based
    medial modeling and multi-atlas label fusion techniques to automatically
    delineate and quantitatively describe aortic leaflet geometry in
    3D echocardiographic (3DE) images, a challenging task that has been
    explored only to a limited extent. The method makes use of expert
    knowledge of aortic leaflet image appearance, generates segmentations
    with consistent topology, and establishes a shape-based coordinate
    system on the aortic leaflets that enables standardized automated
    measurements. In this study, the algorithm is evaluated on 11 3DE
    images of normal human aortic leaflets acquired at mid systole. The
    clinical relevance of the method is its ability to capture leaflet
    geometry in 3DE image data with minimal user interaction while producing
    consistent measurements of 3D aortic leaflet geometry.},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA}, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pmid = {24505702},
    timestamp = {2014.02.27}
    }
  • G. Song, Y. Liu, B. Wu, B. B. Avants, and J. C. Gee, “Using region trajectories to construct an accurate and efficient polyaffine transform model,” in Information Processing in Medical Imaging, 2013, pp. 668-679.
    [Bibtex]
    @INPROCEEDINGS{Song2013IPMI,
    author = {Song, Gang and Liu, Yang and Wu, Baohua and Avants, Brian B. and
    Gee, James C.},
    title = {{U}sing region trajectories to construct an accurate and efficient
    polyaffine transform model},
    booktitle = {{I}nformation {P}rocessing in {M}edical {I}maging},
    year = {2013},
    pages = {668-679},
    url = {http://dx.doi.org/10.1007/978-3-642-38868-2_56}
    }
  • N. J. Tustison, B. B. Avants, P. A. Cook, J. C. Gee, and J. R. Stone, “Statistical bias in optimized VBM,” in SPIE Medical Imaging, 2013, p. 86720U–86720U.
    [Bibtex]
    @INPROCEEDINGS{tustison2013statistical,
    author = {Tustison, Nicholas J and Avants, Brian B and Cook, Philip A and Gee,
    James C and Stone, James R},
    title = {{S}tatistical bias in optimized {VBM}},
    booktitle = {{SPIE} {M}edical {I}maging},
    year = {2013},
    pages = {86720U--86720U},
    organization = {International Society for Optics and Photonics},
    owner = {pcook},
    timestamp = {2013.10.22}
    }
  • N. J. Tustison, B. B. Avants, P. A. Cook, G. Song, S. Das, N. van Strien, J. R. Stone, and J. C. Gee, “The ANTs cortical thickness processing pipeline,” in SPIE Medical Imaging, 2013, p. 86720K–86720K.
    [Bibtex]
    @INPROCEEDINGS{tustison2013ants,
    author = {Tustison, Nicholas J and Avants, Brian B and Cook, Philip A and Song,
    Gang and Das, Sandhitsu and van Strien, Niels and Stone, James R
    and Gee, James C},
    title = {{T}he {ANT}s cortical thickness processing pipeline},
    booktitle = {{SPIE} {M}edical {I}maging},
    year = {2013},
    pages = {86720K--86720K},
    organization = {International Society for Optics and Photonics},
    owner = {pcook},
    timestamp = {2013.10.22}
    }
  • [DOI] A. Vossough, C. Limperopoulos, M. E. Putt, A. J. {du Plessis}, P. J. Schwab, J. Wu, J. C. Gee, and D. J. Licht, “Development and validation of a semiquantitative brain maturation score on fetal MR images: initial results.,” Radiology, vol. 268, iss. 1, pp. 200-207, 2013.
    [Bibtex]
    @ARTICLE{Vossough2013R,
    author = {Vossough, Arastoo and Limperopoulos, Catherine and Putt, Mary E.
    and {du Plessis}, Adre J. and Schwab, Peter J. and Wu, Jue and Gee,
    James C. and Licht, Daniel J.},
    title = {{D}evelopment and validation of a semiquantitative brain maturation
    score on fetal {MR} images: initial results.},
    journal = {{R}adiology},
    year = {2013},
    volume = {268},
    pages = {200--207},
    number = {1},
    month = {Jul},
    abstract = {To develop a valid, reliable, and simple-to-use semiquantitative visual
    scale of fetal brain maturation for use in clinical fetal MR imaging
    assessment and interpretation.This is a retrospective assessment
    of data from a previous study that was prospective, institutional
    review board approved, and HIPAA compliant. Forty-eight normal pregnancies
    with a gestational age (GA) of 25 to 35 weeks were studied. A fetal
    total maturation score (fTMS) was developed by utilizing six subscores
    that evaluated cortical sulcation, myelination, and the germinal
    matrix and provided a single combined numerical value to be evaluated
    as a marker of brain maturity. The fTMS was correlated with GA and
    segmented brain volume. A regression model that associated GA based
    on the visual fTMS scoring was determined. The model was validated
    with a leave-one-out cross validation procedure.Mean GA was 29.3
    weeks ± 2.9 (standard deviation) (range, 25.2-35.3 weeks) and mean
    fTMS was 8.6 ± 3.7 (range, 4-16). The intraclass correlation coefficient
    between the three readers (independent and blinded) was 0.948 (P
    < .001). The correlations were as follows: GA and brain volume, r
    = 0.964 (P < .001); fTMS and brain volume, r = 0.970 (P < .001);
    and GA and fTMS, r = 0.975 (P < .001). A regression model to calculate
    GA based on fTMS yielded the following equation: calculated GA (weeks)
    = 22.86 + 0.748 fTMS (P < .001; adjusted R(2) = 0.946). The standard
    error of the model for calculation of fetal GA from the visual fTMS
    scale was ± 4.8 days.If validated further, the fTMS scale might be
    used to assess morphologic brain maturity of fetuses between 25 and
    35 weeks GA on a single-case basis in a clinical setting.},
    doi = {10.1148/radiol.13111715},
    institution = {{D}epartment of {R}adiology, {C}hildren's {H}ospital of {P}hiladelphia,
    324 {S} 34th {S}t, {W}ood 2115, {P}hiladelphia, {PA} 19004, {USA}.
    vossough@e-mail.chop.edu},
    keywords = {Brain Mapping, methods; Brain, embryology; Case-Control Studies; Female;
    Gestational Age; Heart Defects, Congenital; Humans; Longitudinal
    Studies; Magnetic Resonance Imaging, methods; Male; Pregnancy; Regression
    Analysis; Retrospective Studies},
    language = {eng},
    medline-pst = {ppublish},
    owner = {johnwoo},
    pii = {radiol.13111715},
    pmid = {23440324},
    timestamp = {2014.02.11},
    url = {http://dx.doi.org/10.1148/radiol.13111715}
    }
  • [DOI] Z. Wang, S. R. Das, S. X. Xie, S. Arnold, J. A. Detre, D. A. Wolk, and A. D. Initiative, “Arterial spin labeled MRI in prodromal Alzheimer’s disease: A multi-site study.,” Neuroimage Clin, vol. 2, pp. 630-6, 2013.
    [Bibtex]
    @ARTICLE{Wang2013NC,
    author = {Wang, Ze and Das, Sandhitsu R. and Xie, Sharon X. and Arnold, Steven
    E. and Detre, John A. and Wolk, David A. and Alzheimer's Disease
    Neuroimaging Initiative},
    title = {{A}rterial spin labeled {MRI} in prodromal {A}lzheimer's disease:
    {A} multi-site study.},
    journal = {{N}euroimage {C}lin},
    year = {2013},
    volume = {2},
    pages = {630-6},
    abstract = {We examined differences in cerebral blood flow (CBF) measured by Arterial
    Spin Labeled perfusion MRI (ASL MRI) across the continuum from cognitively
    normal (CN) older adults to mild Alzheimer's Disease (AD) using data
    from the multi-site Alzheimer's Disease Neuroimaging Initiative (ADNI).
    Measures of CBF, in a predetermined set of regions (meta-ROI), and
    hippocampal volume were compared between CN (n=47), patients with
    early and late Mild Cognitive Impairment [EMCI (n=32), LMCI (n=35)],
    and AD (n=15). Associations between these measures and disease severity,
    assessed by Clinical Dementia Rating scale sum of boxes (CDR SB),
    were also assessed. Mean meta-ROI CBF was associated with group status
    and significant hypoperfusion was observed in LMCI and AD relative
    to CN. Hippocampal volume was associated with group status, but only
    AD patients had significantly smaller volumes than the CN. When examining
    the relationship between these measures and disease severity, both
    were significantly associated with CDR SB and appeared to provide
    independent prediction of status. In light of the tight link between
    CBF and metabolism, ASL MRI represents a promising functional biomarker
    for early diagnosis and disease tracking in AD and this study is
    the first to demonstrate the feasibility in a multi-site context
    in this population. Combining functional and structural measures,
    which can be acquired in the same scanning session, appears to provide
    additional information about disease severity relative to either
    measure alone},
    address = {Netherlands},
    doi = {10.1016/j.nicl.2013.04.014},
    issn = {2213-1582},
    owner = {srdas},
    pii = {S2213-1582(13)00053-3},
    pmcid = {PMC3777751},
    pubmedid = {24179814},
    timestamp = {2014.02.19},
    us_nlm_id = {101597070},
    uuid = {C6FEFB83-AE05-43E3-87AA-652845568627},
    web_data_source = {PubMed}
    }

2012

  • D. Adler, S. Kadivar, J. Pluta, S. Orozco, and P. Yushkevich, “High-resolution atlas of the human hippocampus from postmortem 9.4T MRI and reconstructed histology,” in 18th annual meeting for the Organization of Human Brain Mapping, 2012.
    [Bibtex]
    @INPROCEEDINGS{Adler2012HBM,
    author = {Adler, D. and Kadivar, S. and Pluta, J. and Orozco, S. and Yushkevich,
    P.},
    title = {{H}igh-resolution atlas of the human hippocampus from postmortem
    {9.4T MRI} and reconstructed histology},
    booktitle = {18th annual meeting for the {O}rganization of {H}uman {B}rain {M}apping},
    year = {2012}
    }
  • D. H. Adler, A. Y. Liu, J. Pluta, S. Kadivar, S. Orozco, H. Wang, J. C. Gee, B. B. Avants, and P. A. Yushkevich, “Reconstruction of the human hippocampus in 3D from histology and high-resolution ex-vivo MRI,” in Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on, 2012, pp. 294-297.
    [Bibtex]
    @INPROCEEDINGS{Adler2012ISBI,
    author = {Adler, Daniel H. and Liu, Alex Yang and Pluta, John and Kadivar,
    Salmon and Orozco, Sylvia and Wang, Hongzhi and Gee, James C. and
    Avants, Brian B. and Yushkevich, Paul A.},
    title = {{R}econstruction of the human hippocampus in {3D} from histology
    and high-resolution ex-vivo {MRI}},
    booktitle = {{B}iomedical {I}maging {(ISBI)}, 2012 9th {IEEE} {I}nternational
    {S}ymposium on},
    year = {2012},
    pages = {294--297}
    }
  • [DOI] S. Ash, C. McMillan, R. G. Gross, P. Cook, D. Gunawardena, B. Morgan, A. Boller, A. Siderowf, and M. Grossman, “Impairments of speech fluency in Lewy body spectrum disorder.,” Brain Lang, vol. 120, iss. 3, pp. 290-302, 2012.
    [Bibtex]
    @ARTICLE{Ash2012BL,
    author = {Ash, Sharon and McMillan, Corey and Gross, Rachel G. and Cook, Philip
    and Gunawardena, Delani and Morgan, Brianna and Boller, Ashley and
    Siderowf, Andrew and Grossman, Murray},
    title = {{I}mpairments of speech fluency in {L}ewy body spectrum disorder.},
    journal = {{B}rain {L}ang},
    year = {2012},
    volume = {120},
    pages = {290--302},
    number = {3},
    month = {Mar},
    abstract = {Few studies have examined connected speech in demented and non-demented
    patients with Parkinson's disease (PD). We assessed the speech production
    of 35 patients with Lewy body spectrum disorder (LBSD), including
    non-demented PD patients, patients with PD dementia (PDD), and patients
    with dementia with Lewy bodies (DLB), in a semi-structured narrative
    speech sample in order to characterize impairments of speech fluency
    and to determine the factors contributing to reduced speech fluency
    in these patients. Both demented and non-demented PD patients exhibited
    reduced speech fluency, characterized by reduced overall speech rate
    and long pauses between sentences. Reduced speech rate in LBSD correlated
    with measures of between-utterance pauses, executive functioning,
    and grammatical comprehension. Regression analyses related non-fluent
    speech, grammatical difficulty, and executive difficulty to atrophy
    in frontal brain regions. These findings indicate that multiple factors
    contribute to slowed speech in LBSD, and this is mediated in part
    by disease in frontal brain regions.},
    doi = {10.1016/j.bandl.2011.09.004},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania {S}chool
    of {M}edicine, {U}nited {S}tates. ash@mail.med.upenn.edu},
    keywords = {Aged; Aged, 80 and over; Corpus Striatum, physiopathology; Female;
    Humans; Lewy Body Disease, complications/physiopathology; Linguistics;
    Male; Middle Aged; Narration; Neuropsychological Tests; Parkinson
    Disease, complications/physiopathology; Prefrontal Cortex, physiopathology;
    Speech Disorders, diagnosis/etiology/physiopathology; Speech Production
    Measurement; Speech, physiology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0093-934X(11)00157-X},
    pmid = {22099969},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.bandl.2011.09.004}
    }
  • B. Avants, P. Dhillon, B. M. Kandel, P. A. Cook, C. T. McMillan, M. Grossman, and J. C. Gee, “Eigenanatomy improves detection power for longitudinal cortical change.,” Med Image Comput Comput Assist Interv, vol. 15, iss. Pt 3, pp. 206-213, 2012.
    [Bibtex]
    @ARTICLE{Avants2012MICCAI,
    author = {Avants, Brian and Dhillon, Paramveer and Kandel, Benjamin M. and
    Cook, Philip A. and McMillan, Corey T. and Grossman, Murray and Gee,
    James C.},
    title = {{E}igenanatomy improves detection power for longitudinal cortical
    change.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2012},
    volume = {15},
    pages = {206--213},
    number = {Pt 3},
    abstract = {We contribute a novel and interpretable dimensionality reduction strategy,
    eigenanatomy, that is tuned for neuroimaging data. The method approximates
    the eigendecomposition of an image set with basis functions (the
    eigenanatomy vectors) that are sparse, unsigned and are anatomically
    clustered. We employ the eigenanatomy vectors as anatomical predictors
    to improve detection power in morphometry. Standard voxel-based morphometry
    (VBM) analyzes imaging data voxel-by-voxel--and follows this with
    cluster-based or voxel-wise multiple comparisons correction methods
    to determine significance. Eigenanatomy reverses the standard order
    of operations by first clustering the voxel data and then using standard
    linear regression in this reduced dimensionality space. As with traditional
    region-of-interest (ROI) analysis, this strategy can greatly improve
    detection power. Our results show that eigenanatomy provides a principled
    objective function that leads to localized, data-driven regions of
    interest. These regions improve our ability to quantify biologically
    plausible rates of cortical change in two distinct forms of neurodegeneration.
    We detail the algorithm and show experimental evidence of its efficacy.},
    institution = {{P}hiladelphia, {PA} 19104, {USA}.},
    keywords = {Aging, physiology; Algorithms; Brain, anatomy /&/ histology/physiology;
    Humans; Image Enhancement, methods; Image Interpretation, Computer-Assisted,
    methods; Information Storage and Retrieval, methods; Longitudinal
    Studies; Magnetic Resonance Imaging, methods; Pattern Recognition,
    Automated, methods; Reproducibility of Results; Sensitivity and Specificity},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {23286132},
    timestamp = {2013.02.19}
    }
  • B. B. Avants, N. J. Tustison, G. Song, B. Wu, M. Stauffer, M. McCormick, H. J. Johnson, and J. C. Gee, “A unified image registration framework for ITK,” in Biomedical Image Registration – 5th International Workshop, 2012, pp. 266-275.
    [Bibtex]
    @INPROCEEDINGS{Avants2012WBIR,
    author = {Avants, Brian B. and Tustison, Nicholas J. and Song, Gang and Wu,
    Baohua and Stauffer, Michael and McCormick, Matthew and Johnson,
    Hans J. and Gee, James C.},
    title = {{A} unified image registration framework for {ITK}},
    booktitle = {{B}iomedical {I}mage {R}egistration - 5th {I}nternational {W}orkshop},
    year = {2012},
    pages = {266-275},
    url = {http://dx.doi.org/10.1007/978-3-642-31340-0_28}
    }
  • A. Azarion, J. Wu, A. Pearce, J. Wagenaar, K. Davis, Y. Zheng, H. Wang, B. Litt, and J. Gee, “An Open-Source Pipeline for Visualization of Intracranially Implanted Electrodes Using 3D CT-MRI Co-Registration,” in American Epilepsy Society Annual Meeting 2012, Epilepsy Currents online supplement, San Diego, San Diego, USA, 2012, p. Poster No. 1.375.
    [Bibtex]
    @INPROCEEDINGS{Azarion2012,
    author = {A. Azarion and J. Wu and A. Pearce and J. Wagenaar and K. Davis and
    Y. Zheng and H. Wang and B. Litt and J. Gee},
    title = {{A}n {O}pen-{S}ource {P}ipeline for {V}isualization of {I}ntracranially
    {I}mplanted {E}lectrodes {U}sing 3{D} {CT}-{MRI} {C}o-{R}egistration},
    booktitle = {{A}merican {E}pilepsy {S}ociety {A}nnual {M}eeting 2012, {E}pilepsy
    {C}urrents online supplement, {S}an {D}iego},
    year = {2012},
    volume = {1},
    pages = {Poster No. 1.375},
    address = {San Diego, USA},
    owner = {johnwoo},
    timestamp = {2014.02.12}
    }
  • R. Crescenzi, D. Adler, P. A. Yushkevich, V. M. -Y. Lee, J. A. Detre, and A. Borthakur, “Early diffusion changes in a mouse model of neurofibrillary tangles,” in Proceedings 21st Scientific Meeting, International Society for Magnetic Resonance in Medicine, Melbourne, 2012, p. 975.
    [Bibtex]
    @INPROCEEDINGS{Crescenzi2012ISMRM,
    author = {Crescenzi, R. and Adler, D. and Yushkevich, P. A. and Lee, V. M.-Y.
    and Detre, J. A. and Borthakur, A.},
    title = {{E}arly diffusion changes in a mouse model of neurofibrillary tangles},
    booktitle = {{P}roceedings 21st {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {M}elbourne},
    year = {2012},
    pages = {975}
    }
  • [DOI] S. R. Das, B. B. Avants, J. Pluta, H. Wang, J. W. Suh, M. W. Weiner, S. Mueller, and P. A. Yushkevich, “Measuring longitudinal change in the hippocampal formation from in vivo high-resolution T2-weighted MRI.,” Neuroimage, 2012.
    [Bibtex]
    @ARTICLE{Das2012N,
    author = {Das, Sandhitsu R. and Avants, Brian B. and Pluta, John and Wang,
    Hongzhi and Suh, Jung Wook and Weiner, Michael W. and Mueller, Susanne
    G. and Yushkevich, Paul A.},
    title = {{M}easuring longitudinal change in the hippocampal formation from
    in vivo high-resolution {T}2-weighted {MRI}.},
    journal = {{N}euroimage},
    year = {2012},
    month = {1},
    abstract = {The hippocampal formation (HF) is a brain structure of great interest
    because of its central role in learning and memory, and its associated
    vulnerability to several neurological disorders. In vivo oblique
    coronal T2-weighted MRI with high in-plane resolution (0.5mm$\times$0.5mm),
    thick slices (2.0mm), and a field of view tailored to imaging the
    hippocampal formation (denoted HF-MRI in this paper) has been advanced
    as a useful imaging modality for detailed hippocampal morphometry.
    Cross-sectional analysis of volume measurements derived from HF-MRI
    has shown the modality's promise to yield sensitive imaging-based
    biomarker for neurological disorders such as Alzheimer's disease.
    However, the utility of this modality for making measurements of
    longitudinal change has not yet been demonstrated. In this paper,
    using an unbiased deformation-based morphometry (DBM) pipeline, we
    examine the suitability of HF-MRI for estimating longitudinal change
    by comparing atrophy rates measured in the whole hippocampus from
    this modality with those measured from more common isotropic (1mm(3))
    T1-weighted MRI in the same set of individuals, in a cohort of healthy
    controls and patients with cognitive impairment. While measurements
    obtained from HF-MRI were largely consistent with those obtained
    from T1-MRI, HF-MRI yielded slightly larger group effect of greater
    atrophy rates in patients than in controls. The estimated minimum
    sample size required for detecting a 25\% change in patients' atrophy
    rate in the hippocampus compared to the control group with a statistical
    power $\beta$=0.8 was N=269. For T1-MRI, the equivalent sample size
    was N=325. Using a dataset of test-retest scans, we show that the
    measurements were free of additive bias. We also demonstrate that
    these results were not a confound of certain methodological choices
    made in the DBM pipeline to address the challenges of making longitudinal
    measurements from HF-MRI, using a region of interest (ROI) around
    the HF to globally align serial images, followed by slice-by-slice
    deformable registration to measure local volume change. Additionally,
    we present a preliminary study of atrophy rate measurements within
    hippocampal subfields using HF-MRI. Cross-sectional differences in
    atrophy rates were detected in several subfields.},
    doi = {10.1016/j.neuroimage.2012.01.098},
    issn = {1095-9572},
    organization = {Penn Image Computing and Science Laboratory (PICSL), Department of
    Radiology, University of Pennsylvania, Philadelphia, PA, USA.},
    owner = {srdas},
    pii = {S1053-8119(12)00115-2},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {22306801},
    timestamp = {2014.02.19},
    us_nlm_id = {9215515},
    uuid = {D77422CD-5A46-4525-9886-3D83793F237C},
    web_data_source = {PubMed}
    }
  • [DOI] R. Datta, J. Lee, J. Duda, B. Avants, C. H. Vite, B. Tseng, J. C. Gee, G. D. Aguirre, and G. K. Aguirre, “A digital atlas of the dog brain.,” PLoS One, vol. 7, iss. 12, p. e52140, 2012.
    [Bibtex]
    @ARTICLE{Datta2012,
    author = {Datta, Ritobrato and Lee, Jongho and Duda, Jeffrey and Avants, Brian
    B. and Vite, Charles H. and Tseng, Ben and Gee, James C. and Aguirre,
    Gustavo D. and Aguirre, Geoffrey K.},
    title = {{A} digital atlas of the dog brain.},
    journal = {{PL}o{S} {O}ne},
    year = {2012},
    volume = {7},
    pages = {e52140},
    number = {12},
    abstract = {There is a long history and a growing interest in the canine as a
    subject of study in neuroscience research and in translational neurology.
    In the last few years, anatomical and functional magnetic resonance
    imaging (MRI) studies of awake and anesthetized dogs have been reported.
    Such efforts can be enhanced by a population atlas of canine brain
    anatomy to implement group analyses. Here we present a canine brain
    atlas derived as the diffeomorphic average of a population of fifteen
    mesaticephalic dogs. The atlas includes: 1) A brain template derived
    from in-vivo, T1-weighted imaging at 1 mm isotropic resolution at
    3 Tesla (with and without the soft tissues of the head); 2) A co-registered,
    high-resolution (0.33 mm isotropic) template created from imaging
    of ex-vivo brains at 7 Tesla; 3) A surface representation of the
    gray matter/white matter boundary of the high-resolution atlas (including
    labeling of gyral and sulcal features). The properties of the atlas
    are considered in relation to historical nomenclature and the evolutionary
    taxonomy of the Canini tribe. The atlas is available for download
    (https://cfn.upenn.edu/aguirre/wiki/public:data_plosone_2012_datta).},
    doi = {10.1371/journal.pone.0052140},
    institution = {{D}epartment of {N}eurology, {S}chool of {M}edicine, {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {P}ennsylvania, {USA}.},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pii = {PONE-D-12-25989},
    pmid = {23284904},
    timestamp = {2013.05.31},
    url = {http://dx.doi.org/10.1371/journal.pone.0052140}
    }
  • [DOI] P. Dhillon, B. Avants, L. Ungar, and J. Gee, “Partial Sparse Canonical Correlation Analysis (PSCCA) for population studies in Medical Imaging,” in Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on, 2012, pp. 1132-1135.
    [Bibtex]
    @INPROCEEDINGS{Dhillon2012ISBI,
    author = {Paramveer Dhillon and Brian Avants and Lyle Ungar and James Gee},
    title = {{P}artial {S}parse {C}anonical {C}orrelation {A}nalysis {(PSCCA)}
    for population studies in {M}edical {I}maging},
    booktitle = {{B}iomedical {I}maging {(ISBI)}, 2012 9th {IEEE} {I}nternational
    {S}ymposium on},
    year = {2012},
    pages = {1132--1135},
    doi = {10.1109/ISBI.2012.6235759},
    timestamp = {2014.02.14},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6235759}
    }
  • J. T. Duda, D. J. J. Wang, E. Kilroy, J. C. Gee, and B. B. Avants, “Relating cerebral blood flow to structural and functional metrics in typically developing children,” in Proceedings of Perfusion MRI: Standardization, Beyond CBF and Everyday Clinical Applications, International Society for Magnetic Resonance in Medicine Scientific Workshop, Amsterdam, 2012, p. 40.
    [Bibtex]
    @INPROCEEDINGS{Duda2012ISMRMASL,
    author = {Duda, Jeffrey T. and Wang, Danny J.J. and Kilroy, Emily and Gee,
    James C. and Avants, Brian B.},
    title = {{R}elating cerebral blood flow to structural and functional metrics
    in typically developing children},
    booktitle = {{P}roceedings of {P}erfusion {MRI}: {S}tandardization, {B}eyond {CBF}
    and {E}veryday {C}linical {A}pplications, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine {S}cientific {W}orkshop,
    {A}msterdam},
    year = {2012},
    pages = {40}
    }
  • [DOI] R. G. Gross, C. T. McMillan, K. Chandrasekaran, M. Dreyfuss, S. Ash, B. Avants, P. Cook, P. Moore, D. J. Libon, A. Siderowf, and M. Grossman, “Sentence processing in Lewy body spectrum disorder: the role of working memory.,” Brain Cogn, vol. 78, iss. 2, pp. 85-93, 2012.
    [Bibtex]
    @ARTICLE{Gross2012BC,
    author = {Gross, Rachel G. and McMillan, Corey T. and Chandrasekaran, Keerthi
    and Dreyfuss, Michael and Ash, Sharon and Avants, Brian and Cook,
    Philip and Moore, Peachie and Libon, David J. and Siderowf, Andrew
    and Grossman, Murray},
    title = {{S}entence processing in {L}ewy body spectrum disorder: the role
    of working memory.},
    journal = {{B}rain {C}ogn},
    year = {2012},
    volume = {78},
    pages = {85--93},
    number = {2},
    month = {Mar},
    abstract = {Prior work has related sentence processing to executive deficits in
    non-demented patients with Parkinson's disease (PD). We extended
    this investigation to patients with dementia with Lewy bodies (DLB)
    and PD dementia (PDD) by examining grammatical and working memory
    components of sentence processing in the full range of patients with
    Lewy body spectrum disorder (LBSD). Thirty-three patients with LBSD
    were given a two-alternative, forced-choice sentence-picture matching
    task. Sentence type, working memory, and grammatical structure were
    systematically manipulated in the sentences. We found that patients
    with PDD and DLB were significantly impaired relative to non-demented
    PD patients and healthy controls. The deficit in PDD/DLB was most
    pronounced for sentences lengthened by the strategic placement of
    an additional prepositional phrase and for sentences with an additional
    proposition due to a center-embedded clause. However, there was no
    effect for subject-relative versus object-relative grammatical structure.
    An MRI voxel-based morphometry analysis in a subset of patients showed
    significant gray matter thinning in the frontal lobe bilaterally,
    and this extended to temporal, parietal and occipital regions. A
    regression analysis related sentence processing difficulty in LBSD
    to frontal neocortex, including inferior prefrontal, premotor, and
    dorsolateral prefrontal regions, as well as right superior temporal
    cortex. These findings are consistent with the hypothesis that patients
    with PDD and DLB have difficulty processing sentences with increased
    working memory demands and that this deficit is related in part to
    their frontal disease.},
    doi = {10.1016/j.bandc.2011.12.004},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania {S}chool
    of {M}edicine, {U}nited {S}tates.},
    keywords = {Aged; Case-Control Studies; Executive Function; Humans; Language;
    Lewy Body Disease, psychology; Memory, Short-Term; Mental Recall;
    Neuropsychological Tests; Photic Stimulation; Stroop Test},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0278-2626(11)00231-4},
    pmid = {22218297},
    timestamp = {2013.04.23},
    url = {http://dx.doi.org/10.1016/j.bandc.2011.12.004}
    }
  • [DOI] M. Grossman, R. G. Gross, P. Moore, M. Dreyfuss, C. T. McMillan, P. A. Cook, S. Ash, and A. Siderowf, “Difficulty processing temporary syntactic ambiguities in Lewy body spectrum disorder.,” Brain Lang, vol. 120, iss. 1, pp. 52-60, 2012.
    [Bibtex]
    @ARTICLE{Grossman2012BL,
    author = {Grossman, Murray and Gross, Rachel G. and Moore, Peachie and Dreyfuss,
    Michael and McMillan, Corey T. and Cook, Philip A. and Ash, Sherry
    and Siderowf, Andrew},
    title = {{D}ifficulty processing temporary syntactic ambiguities in {L}ewy
    body spectrum disorder.},
    journal = {{B}rain {L}ang},
    year = {2012},
    volume = {120},
    pages = {52--60},
    number = {1},
    month = {Jan},
    abstract = {While grammatical aspects of language are preserved, executive deficits
    are prominent in Lewy body spectrum disorder (LBSD), including Parkinson's
    disease (PD), Parkinson's dementia (PDD) and dementia with Lewy bodies
    (DLB). We examined executive control during sentence processing in
    LBSD by assessing temporary structural ambiguities. Using an on-line
    word detection procedure, patients heard sentences with a syntactic
    structure that has high-compatibility or low-compatibility with the
    main verb's statistically preferred syntactic structure, and half
    of the sentences were lengthened strategically between the onset
    of the ambiguity and its resolution. We found selectively slowed
    processing of lengthened ambiguous sentences in the PDD/DLB subgroup.
    This correlated with impairments on measures of executive control.
    Regression analyses related the working memory deficit during ambiguous
    sentence processing to significant cortical thinning in frontal and
    parietal regions. These findings emphasize the role of prefrontal
    disease in the executive limitations that interfere with processing
    ambiguous sentences in LBSD.},
    doi = {10.1016/j.bandl.2011.08.007},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania {S}chool
    of {M}edicine, {U}nited {S}tates. mgrossma@mail.med.upenn.edu},
    keywords = {Aged; Female; Humans; Language; Lewy Body Disease, physiopathology;
    Magnetic Resonance Imaging; Male; Speech Perception, physiology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0093-934X(11)00153-2},
    pmid = {21962945},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.bandl.2011.08.007}
    }
  • [DOI] V. Jain, J. Duda, B. Avants, M. Giannetta, S. X. Xie, T. Roberts, J. A. Detre, H. Hurt, F. W. Wehrli, and D. J. J. Wang, “Longitudinal reproducibility and accuracy of pseudo-continuous arterial spin-labeled perfusion MR imaging in typically developing children.,” Radiology, vol. 263, iss. 2, pp. 527-536, 2012.
    [Bibtex]
    @ARTICLE{Jain2012,
    author = {Jain, Varsha and Duda, Jeffrey and Avants, Brian and Giannetta, Mariel
    and Xie, Sharon X. and Roberts, Timothy and Detre, John A. and Hurt,
    Hallam and Wehrli, Felix W. and Wang, Danny J J.},
    title = {{L}ongitudinal reproducibility and accuracy of pseudo-continuous
    arterial spin-labeled perfusion {MR} imaging in typically developing
    children.},
    journal = {{R}adiology},
    year = {2012},
    volume = {263},
    pages = {527--536},
    number = {2},
    month = {May},
    abstract = {To evaluate the longitudinal repeatability and accuracy of cerebral
    blood flow (CBF) measurements by using pseudo-continuous arterial
    spin-labeled (pCASL) perfusion magnetic resonance (MR) imaging in
    typically developing children.Institutional review board approval
    with HIPAA compliance and informed consent were obtained. Twenty-two
    children aged 7-17 years underwent repeated pCASL examinations 2-4
    weeks apart with a 3-T MR imager, along with in vivo blood T1 and
    arterial transit time measurements. Phase-contrast (PC) MR imaging
    was performed as the reference standard for global blood flow volume.
    Intraclass correlation coefficient (ICC) and within-subject coefficient
    of variation (wsCV) were used to evaluate accuracy and repeatability.The
    accuracy of pCASL against the reference standard of PC MR imaging
    increased on incorporating subjectwise in vivo blood T1 measurement
    (ICC: 0.32 vs 0.58). The ICC further increased to 0.65 by using a
    population-based model of blood T1. Additionally, CBF measurements
    with use of pCASL demonstrated a moderate to good level of longitudinal
    repeatability in whole brain (ICC = 0.61, wsCV = 15\%), in gray matter
    (ICC = 0.65, wsCV = 14\%), and across 16 brain regions (mean ICC
    = 0.55, wsCV = 17\%). The mean arterial transit time was 1538 msec
    ± 123 (standard deviation) in the pediatric cohort studied, which
    showed an increasing trend with age (P = .043).Incorporating developmental
    changes in blood T1 is important for improving the accuracy of pCASL
    CBF measurements in children and adolescents; the noninvasive nature,
    accuracy, and longitudinal repeatability should facilitate the use
    of pCASL perfusion MR imaging in neurodevelopmental studies.},
    doi = {10.1148/radiol.12111509},
    institution = {{D}epartment of {R}adiology and {B}iostatistics, {U}niversity of
    {P}ennsylvania {M}edical {C}enter, {P}hiladelphia, {PA}, {USA}.},
    keywords = {Adolescent; Artifacts; Blood Volume; Brain Mapping, methods; Brain,
    growth /&/ development; Cerebrovascular Circulation; Child; Female;
    Humans; Image Enhancement, methods; Image Processing, Computer-Assisted,
    methods; Magnetic Resonance Imaging, methods; Male; Prospective Studies;
    Reference Values; Reproducibility of Results; Spin Labels},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pii = {263/2/527},
    pmid = {22517961},
    timestamp = {2013.05.31},
    url = {http://dx.doi.org/10.1148/radiol.12111509}
    }
  • G. M. Lawson, J. T. Duda, J. Wu, B. B. Avants, and M. J. Farah, “Association between socioeconomic status and cortical thickness in prefrontal cortical subregions,” in Society for Neuroscience Annual Meeting, New Orleans, LA, 2012.
    [Bibtex]
    @INPROCEEDINGS{Lawson2012,
    author = {G. M. Lawson and J. T. Duda and J. Wu and B. B. Avants and M. J.
    Farah},
    title = {{A}ssociation between socioeconomic status and cortical thickness
    in prefrontal cortical subregions},
    booktitle = {{S}ociety for {N}euroscience {A}nnual {M}eeting, {N}ew {O}rleans,
    {LA}},
    year = {2012},
    month = {Oct},
    confidential = {n},
    owner = {johnwoo},
    timestamp = {2013.05.31}
    }
  • [DOI] C. Li, M. C. Langham, C. L. Epstein, J. F. Magland, J. Wu, J. Gee, and F. W. Wehrli, “Accuracy of the cylinder approximation for susceptometric measurement of intravascular oxygen saturation.,” Magn Reson Med, vol. 67, iss. 3, pp. 808-813, 2012.
    [Bibtex]
    @ARTICLE{Li2012MRM,
    author = {Li, Cheng and Langham, Michael C. and Epstein, Charles L. and Magland,
    Jeremy F. and Wu, Jue and Gee, James and Wehrli, Felix W.},
    title = {{A}ccuracy of the cylinder approximation for susceptometric measurement
    of intravascular oxygen saturation.},
    journal = {{M}agn {R}eson {M}ed},
    year = {2012},
    volume = {67},
    pages = {808--813},
    number = {3},
    month = {Mar},
    abstract = {Susceptometry-based MR oximetry has previously been shown suitable
    for quantifying hemoglobin oxygen saturation in large vessels for
    studying vascular reactivity and quantification of global cerebral
    metabolic rate of oxygen utilization. A key assumption underlying
    this method is that large vessels can be modeled as long paramagnetic
    cylinders. However, bifurcations, tapering, noncircular cross-section,
    and curvature of these vessels produce substantial deviations from
    cylindrical geometry, which may lead to errors in hemoglobin oxygen
    saturation quantification. Here, the accuracy of the "long cylinder"
    approximation is evaluated via numerical computation of the induced
    magnetic field from 3D segmented renditions of three veins of interest
    (superior sagittal sinus, femoral and jugular vein). At a typical
    venous oxygen saturation of 65\%, the absolute error in hemoglobin
    oxygen saturation estimated via a closed-form cylinder approximation
    was 2.6\% hemoglobin oxygen saturation averaged over three locations
    in the three veins studied and did not exceed 5\% for vessel tilt
    angles <30° at any one location. In conclusion, the simulation results
    provide a significant level of confidence for the validity of the
    cylinder approximation underlying MR susceptometry-based oximetry
    of large vessels.},
    doi = {10.1002/mrm.23034},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {P}ennsylvania 19104, {USA}.},
    keywords = {Adult; Algorithms; Femoral Vein; Humans; Image Processing, Computer-Assisted;
    Jugular Veins; Magnetic Resonance Imaging, methods; Male; Oximetry,
    methods; Oxygen, blood; Superior Sagittal Sinus},
    language = {eng},
    medline-pst = {ppublish},
    owner = {johnwoo},
    pmid = {21858859},
    timestamp = {2013.01.31},
    url = {http://dx.doi.org/10.1002/mrm.23034}
    }
  • [DOI] J. Pluta, P. Yushkevich, S. Das, and D. Wolk, “In vivo Analysis of Hippocampal Subfield Atrophy in Mild Cognitive Impairment via Semi-Automatic Segmentation of T2-Weighted MRI.,” J Alzheimers Dis, vol. 31, iss. 1, pp. 85-99, 2012.
    [Bibtex]
    @ARTICLE{Pluta2012JAD,
    author = {Pluta, John and Yushkevich, Paul and Das, Sandhitsu and Wolk, David},
    title = {{I}n vivo {A}nalysis of {H}ippocampal {S}ubfield {A}trophy in {M}ild
    {C}ognitive {I}mpairment via {S}emi-{A}utomatic {S}egmentation of
    {T}2-{W}eighted {MRI}.},
    journal = {{J} {A}lzheimers {D}is},
    year = {2012},
    volume = {31},
    pages = {85-99},
    number = {1},
    month = {4},
    abstract = {The measurement of hippocampal volumes using MRI is a useful in-vivo
    biomarker for detection and monitoring of early Alzheimer's disease
    (AD), including during the amnestic mild cognitive impairment (a-MCI)
    stage. The pathology underlying AD has regionally selective effects
    within the hippocampus. As such, we predict that hippocampal subfields
    are more sensitive in discriminating prodromal AD (i.e., a-MCI) from
    cognitively normal controls than whole hippocampal volumes, and attempt
    to demonstrate this using a semi-automatic method that can accurately
    segment hippocampal subfields. High-resolution coronal-oblique T2-weighted
    images of the hippocampal formation were acquired in 45 subjects
    (28 controls and 17 a-MCI (mean age: 69.5 9.2; 70.2 7.6)). CA1, CA2,
    CA3, and CA4/DG subfields, along with head and tail regions, were
    segmented using an automatic algorithm. CA1 and CA4/DG segmentations
    were manually edited. Whole hippocampal volumes were obtained from
    the subjects' T1-weighted anatomical images. Automatic segmentation
    produced significant group differences in the following subfields:
    CA1 (left: p = 0.001, right: p = 0.038), CA4/DG (left: p = 0.002,
    right: p = 0.043), head (left: p = 0.018, right: p = 0.002), and
    tail (left: p = 0.019). After manual correction, differences were
    increased in CA1 (left: p < 0.001, right: p = 0.002), and reduced
    in CA4/DG (left: p = 0.029, right: p = 0.221). Whole hippocampal
    volumes significantly differed bilaterally (left: p = 0.028, right:
    p = 0.009). This pattern of atrophy in a-MCI is consistent with the
    topography of AD pathology observed in postmortem studies, and corrected
    left CA1 provided stronger discrimination than whole hippocampal
    volume (p = 0.03). These results suggest that semi-automatic segmentation
    of hippocampal subfields is efficient and may provide additional
    sensitivity beyond whole hippocampal volumes},
    address = {Netherlands},
    citation_identifier = {Pluta 2012},
    doi = {10.3233/JAD-2012-111931},
    endnote_reference_number = {95},
    issn = {1875-8908},
    keywords = {Humans;Area Under Curve;Functional Laterality;Female;Hippocampus;Atrophy;ROC
    Curve;Male;Magnetic Resonance Imaging;Case-Control Studies;research
    support, n.i.h., extramural;Automatic Data Processing;Chi-Square
    Distribution;video-audio media;Mild Cognitive Impairment},
    mid = {NIHMS366415},
    organization = {Penn Image Computing and Science Laboratory, Department of Radiology,
    University of Pennsylvania, PA, USA Center for Functional Neuroimaging,
    Departments of Neurology and Radiology, University of Pennsylvania,
    Hospital of the University of Pennsylvania, PA, USA.},
    owner = {srdas},
    pii = {74701307X52M342M},
    pmcid = {PMC3391337},
    pubmedid = {22504319},
    sentelink = {file://localhost/Users/srdas/Documents/Sente/My%20Bibliographies/Pluta/J%20Alzheimers%20Dis/2012/Pluta%20J%20Alzheimers%20Dis%202012%20891DCBE5-4580-4CDB-918.pdf,Sente,},
    timestamp = {2014.02.19},
    us_nlm_id = {9814863},
    uuid = {263D90AB-999E-44E6-BFFB-32B71598720A},
    web_data_source = {PubMed}
    }
  • [DOI] A. M. Pouch, H. Wang, P. A. Yushkevich, M. Takabe, B. M. Jackson, J. H. Gorman 3rd, R. C. Gorman, and C. M. Sehgal, Fully automatic segmentation of the open mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas label fusion and deformable medial modeling, 2012.
    [Bibtex]
    @PROCEEDINGS{2012,
    title = {{F}ully automatic segmentation of the open mitral leaflets in {3D}
    transesophageal echocardiographic images using multi-atlas label
    fusion and deformable medial modeling},
    year = {2012},
    author = {Pouch, Alison M. and Wang, Hongzhi and Yushkevich, Paul A. and Takabe,
    Manabu and Jackson, Benjamin M. and Gorman, 3rd, Joseph H. and Gorman,
    Robert C. and Sehgal, Chandra M.},
    booktitle = {{U}ltrasonics {S}ymposium ({IUS}), 2012 {IEEE} {I}nternational},
    doi = {10.1109/ULTSYM.2012.0055},
    owner = {alison},
    pages = {220--223},
    timestamp = {2014.02.27},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6562275}
    }
  • [DOI] A. M. Pouch, C. Xu, P. A. Yushkevich, A. S. Jassar, M. Vergnat, J. H. Gorman 3rd, R. C. Gorman, C. M. Sehgal, and B. M. Jackson, “Semi-automated mitral valve morphometry and computational stress analysis using 3D ultrasound.,” J Biomech, vol. 45, iss. 5, pp. 903-907, 2012.
    [Bibtex]
    @ARTICLE{Pouch2012JB,
    author = {Pouch, Alison M. and Xu, Chun and Yushkevich, Paul A. and Jassar,
    Arminder S. and Vergnat, Mathieu and Gorman, 3rd, Joseph H and Gorman,
    Robert C. and Sehgal, Chandra M. and Jackson, Benjamin M.},
    title = {{S}emi-automated mitral valve morphometry and computational stress
    analysis using 3{D} ultrasound.},
    journal = {{J} {B}iomech},
    year = {2012},
    volume = {45},
    pages = {903--907},
    number = {5},
    month = {Mar},
    abstract = {In vivo human mitral valves (MV) were imaged using real-time 3D transesophageal
    echocardiography (rt-3DTEE), and volumetric images of the MV at mid-systole
    were analyzed by user-initialized segmentation and 3D deformable
    modeling with continuous medial representation, a compact representation
    of shape. The resulting MV models were loaded with physiologic pressures
    using finite element analysis (FEA). We present the regional leaflet
    stress distributions predicted in normal and diseased (regurgitant)
    MVs. Rt-3DTEE, semi-automated leaflet segmentation, 3D deformable
    modeling, and FEA modeling of the in vivo human MV is tenable and
    useful for evaluation of MV pathology.},
    doi = {10.1016/j.jbiomech.2011.11.033},
    institution = {{D}epartment of {B}ioengineering, {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {PA}, {USA}.},
    keywords = {Echocardiography, Three-Dimensional, methods; Echocardiography, Transesophageal,
    methods; Finite Element Analysis; Heart Valve Diseases, pathology/ultrasonography;
    Humans; Image Interpretation, Computer-Assisted, methods; Mitral
    Valve, pathology/ultrasonography; Models, Cardiovascular; Ultrasonics,
    methods},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S0021-9290(11)00715-9},
    pmid = {22281408},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.jbiomech.2011.11.033}
    }
  • [DOI] A. M. Pouch, P. A. Yushkevich, B. M. Jackson, A. S. Jassar, M. Vergnat, J. H. Gorman, R. C. Gorman, and C. M. Sehgal, “Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound.,” Med Phys, vol. 39, iss. 2, pp. 933-950, 2012.
    [Bibtex]
    @ARTICLE{Pouch2012MP,
    author = {Pouch, Alison M. and Yushkevich, Paul A. and Jackson, Benjamin M.
    and Jassar, Arminder S. and Vergnat, Mathieu and Gorman, Joseph H.
    and Gorman, Robert C. and Sehgal, Chandra M.},
    title = {{D}evelopment of a semi-automated method for mitral valve modeling
    with medial axis representation using 3{D} ultrasound.},
    journal = {{M}ed {P}hys},
    year = {2012},
    volume = {39},
    pages = {933--950},
    number = {2},
    month = {Feb},
    abstract = {Precise 3D modeling of the mitral valve has the potential to improve
    our understanding of valve morphology, particularly in the setting
    of mitral regurgitation (MR). Toward this goal, the authors have
    developed a user-initialized algorithm for reconstructing valve geometry
    from transesophageal 3D ultrasound (3D US) image data.Semi-automated
    image analysis was performed on transesophageal 3D US images obtained
    from 14 subjects with MR ranging from trace to severe. Image analysis
    of the mitral valve at midsystole had two stages: user-initialized
    segmentation and 3D deformable modeling with continuous medial representation
    (cm-rep). Semi-automated segmentation began with user-identification
    of valve location in 2D projection images generated from 3D US data.
    The mitral leaflets were then automatically segmented in 3D using
    the level set method. Second, a bileaflet deformable medial model
    was fitted to the binary valve segmentation by Bayesian optimization.
    The resulting cm-rep provided a visual reconstruction of the mitral
    valve, from which localized measurements of valve morphology were
    automatically derived. The features extracted from the fitted cm-rep
    included annular area, annular circumference, annular height, intercommissural
    width, septolateral length, total tenting volume, and percent anterior
    tenting volume. These measurements were compared to those obtained
    by expert manual tracing. Regurgitant orifice area (ROA) measurements
    were compared to qualitative assessments of MR severity. The accuracy
    of valve shape representation with cm-rep was evaluated in terms
    of the Dice overlap between the fitted cm-rep and its target segmentation.The
    morphological features and anatomic ROA derived from semi-automated
    image analysis were consistent with manual tracing of 3D US image
    data and with qualitative assessments of MR severity made on clinical
    radiology. The fitted cm-reps accurately captured valve shape and
    demonstrated patient-specific differences in valve morphology among
    subjects with varying degrees of MR severity. Minimal variation in
    the Dice overlap and morphological measurements was observed when
    different cm-rep templates were used to initialize model fitting.This
    study demonstrates the use of deformable medial modeling for semi-automated
    3D reconstruction of mitral valve geometry using transesophageal
    3D US. The proposed algorithm provides a parametric geometrical representation
    of the mitral leaflets, which can be used to evaluate valve morphology
    in clinical ultrasound images.},
    doi = {10.1118/1.3673773},
    institution = {{D}epartment of {B}ioengineering, {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {PA} 19104, {USA}. pouch@seas.upenn.edu},
    keywords = {Algorithms; Computer Simulation; Echocardiography, Three-Dimensional,
    methods; Humans; Image Enhancement, methods; Image Interpretation,
    Computer-Assisted, methods; Mitral Valve, anatomy /&/ histology/ultrasonography;
    Models, Anatomic; Models, Cardiovascular; Pattern Recognition, Automated,
    methods; Reproducibility of Results; Sensitivity and Specificity},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pmid = {22320803},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1118/1.3673773}
    }
  • [DOI] J. D. Power, K. A. Barnes, A. Z. Snyder, B. L. Schlaggar, and S. E. Petersen, “Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.,” Neuroimage, vol. 59, iss. 3, pp. 2142-2154, 2012.
    [Bibtex]
    @ARTICLE{Power2012,
    author = {Power, Jonathan D. and Barnes, Kelly A. and Snyder, Abraham Z. and
    Schlaggar, Bradley L. and Petersen, Steven E.},
    title = {{S}purious but systematic correlations in functional connectivity
    {MRI} networks arise from subject motion.},
    journal = {{N}euroimage},
    year = {2012},
    volume = {59},
    pages = {2142--2154},
    number = {3},
    month = {Feb},
    abstract = {Here, we demonstrate that subject motion produces substantial changes
    in the timecourses of resting state functional connectivity MRI (rs-fcMRI)
    data despite compensatory spatial registration and regression of
    motion estimates from the data. These changes cause systematic but
    spurious correlation structures throughout the brain. Specifically,
    many long-distance correlations are decreased by subject motion,
    whereas many short-distance correlations are increased. These changes
    in rs-fcMRI correlations do not arise from, nor are they adequately
    countered by, some common functional connectivity processing steps.
    Two indices of data quality are proposed, and a simple method to
    reduce motion-related effects in rs-fcMRI analyses is demonstrated
    that should be flexibly implementable across a variety of software
    platforms. We demonstrate how application of this technique impacts
    our own data, modifying previous conclusions about brain development.
    These results suggest the need for greater care in dealing with subject
    motion, and the need to critically revisit previous rs-fcMRI work
    that may not have adequately controlled for effects of transient
    subject movements.},
    doi = {10.1016/j.neuroimage.2011.10.018},
    institution = {{D}epartment of {N}eurology, {W}ashington {U}niversity {S}chool of
    {M}edicine, {S}t. {L}ouis, {MO} 63110, {USA}. powerj@wusm.wustl.edu},
    keywords = {Algorithms; Artifacts; Brain, anatomy /&/ histology; Cohort Studies;
    Head Movements; Humans; Image Processing, Computer-Assisted, methods;
    Magnetic Resonance Imaging, instrumentation/methods; Motion; Oxygen,
    blood; Software},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pii = {S1053-8119(11)01181-5},
    pmid = {22019881},
    timestamp = {2015.06.24},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2011.10.018}
    }
  • [DOI] G. Song, E. {Mortani Barbosa} Jr, N. Tustison, W. B. Gefter, M. Kreider, J. C. Gee, and D. A. Torigian, “A comparative study of HRCT image metrics and PFT values for characterization of ILD and COPD.,” Acad Radiol, vol. 19, iss. 7, pp. 857-864, 2012.
    [Bibtex]
    @ARTICLE{Song2012AR,
    author = {Song, Gang and {Mortani Barbosa}, Jr, Eduardo and Tustison, Nicholas
    and Gefter, Warren B. and Kreider, Maryl and Gee, James C. and Torigian,
    Drew A.},
    title = {{A} comparative study of {HRCT} image metrics and {PFT} values for
    characterization of {ILD} and {COPD}.},
    journal = {{A}cad {R}adiol},
    year = {2012},
    volume = {19},
    pages = {857--864},
    number = {7},
    month = {Jul},
    abstract = {The aim of this study was to compare the performance of various image-based
    metrics computed from thoracic high-resolution computed tomography
    (HRCT) with data from pulmonary function testing (PFT) in characterizing
    interstitial lung disease (ILD) and chronic obstructive pulmonary
    disease (COPD).Fourteen patients with ILD and 11 with COPD had undergone
    both PFT and HRCT within 3 days. For each patient, 93 image-based
    metrics were computed, and their relationships with the 21 clinically
    used PFT parameters were analyzed using a minimal-redundancy-maximal-relevance
    statistical framework. The first 20 features were selected among
    the total of 114 mixed image metrics and PFT values in the characterization
    of ILD and COPD.Among the best-performing 20 features, 14 were image
    metrics, derived from attenuation histograms and texture descriptions.
    The highest relevance value computed from PFT parameters was 0.47,
    and the highest from image metrics was 0.52, given the theoretical
    bound as [0, 0.69]. The ILD or COPD classifier using the first four
    features achieved a 1.92\% error rate.Some image metrics are not
    only as good discriminators as PFT for the characterization of ILD
    and COPD but are also not redundant when PFT values are provided.
    Image metrics of attenuation histogram statistics and texture descriptions
    may be valuable for further investigation in computer-assisted diagnosis.},
    doi = {10.1016/j.acra.2012.03.007},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {U}niversity
    of {P}ennsylvania {S}chool of {M}edicine, 3600 {M}arket {S}treet,
    {S}uite 370, {P}hiladelphia, {PA} 19104, {USA}. songgang@seas.upenn.edu},
    keywords = {Female; Humans; Image Processing, Computer-Assisted; Lung Diseases,
    Interstitial, physiopathology/radiography; Male; Middle Aged; Pulmonary
    Disease, Chronic Obstructive, physiopathology/radiography; Respiratory
    Function Tests; Tomography, X-Ray Computed},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S1076-6332(12)00149-3},
    pmid = {22516670},
    timestamp = {2014.07.29},
    url = {http://dx.doi.org/10.1016/j.acra.2012.03.007}
    }
  • [DOI] H. Wang, J. W. Suh, S. R. Das, J. Pluta, C. Craige, and P. A. Yushkevich, “Multi-Atlas Segmentation with Joint Label Fusion.,” IEEE Trans Pattern Anal Mach Intell, 2012.
    [Bibtex]
    @ARTICLE{Wang2012ITPAMI,
    author = {Wang, Hongzhi and Suh, Jung W. and Das, Sandhitsu R. and Pluta, John
    and Craige, Caryne and Yushkevich, Paul A.},
    title = {{M}ulti-{A}tlas {S}egmentation with {J}oint {L}abel {F}usion.},
    journal = {{IEEE} {T}rans {P}attern {A}nal {M}ach {I}ntell},
    year = {2012},
    month = {6},
    abstract = {Multi-atlas segmentation is an effective approach for automatically
    labeling objects of interest in biomedical images. In this approach,
    multiple expert-segmented example images, called \textbackslashemph\{atlases\},
    are registered to a target image, and deformed atlas segmentations
    are combined using \textbackslashemph\{label fusion\}. Among the
    proposed label fusion strategies, weighted voting with spatially
    varying weight distributions derived from atlas-target intensity
    similarity have been particularly successful. However, one limitation
    of these strategies is that the weights are computed independently
    for each atlas, without taking into account the fact that different
    atlases may produce similar label errors. To address this limitation,
    we propose a new solution for the label fusion problem, in which
    weighted voting is formulated in terms of minimizing the total expectation
    of labeling error, and in which pairwise dependency between atlases
    is explicitly modeled as the joint probability of two atlases making
    a segmentation error at a voxel. This probability is approximated
    using intensity similarity between a pair of atlases and the target
    image in the neighborhood of each voxel. We validate our method in
    two medical image segmentation problems: hippocampus segmentation
    and hippocampus subfield segmentation in magnetic resonance (MR)
    images. For both problems, we show consistent and significant improvement
    over label fusion strategies that assign atlas weights independently},
    doi = {10.1109/TPAMI.2012.143},
    issn = {1939-3539},
    organization = {University of Pennsylvania, Philadelphia.},
    owner = {srdas},
    pubmedid = {22732662},
    timestamp = {2014.02.19},
    us_nlm_id = {9885960},
    uuid = {AA2C9232-BA7B-45FF-BBF9-FB18C1713597},
    web_data_source = {PubMed}
    }
  • J. Wu and B. Avants, “Automatic Registration-Based Segmentation for Neonatal Brains Using ANTs and Atropos.” 2012, p. 36.
    [Bibtex]
    @INPROCEEDINGS{Wu2012MGCNBS2N,
    author = {Wu, J. and Avants, B.},
    title = {{A}utomatic {R}egistration-{B}ased {S}egmentation for {N}eonatal
    {B}rains {U}sing {ANT}s and {A}tropos},
    year = {2012},
    pages = {36},
    journal = {{MICCAI} {G}rand {C}hallenge: {N}eonatal {B}rain {S}egmentation 2012
    ({N}eo{B}rain{S}12)},
    owner = {johnwoo},
    timestamp = {2013.01.31}
    }

2011

  • [DOI] S. Ash, C. McMillan, R. G. Gross, P. Cook, B. Morgan, A. Boller, M. Dreyfuss, A. Siderowf, and M. Grossman, “The organization of narrative discourse in Lewy body spectrum disorder.,” Brain Lang, vol. 119, iss. 1, pp. 30-41, 2011.
    [Bibtex]
    @ARTICLE{Ash2011BL,
    author = {Ash, Sharon and McMillan, Corey and Gross, Rachel G. and Cook, Philip
    and Morgan, Brianna and Boller, Ashley and Dreyfuss, Michael and
    Siderowf, Andrew and Grossman, Murray},
    title = {{T}he organization of narrative discourse in {L}ewy body spectrum
    disorder.},
    journal = {{B}rain {L}ang},
    year = {2011},
    volume = {119},
    pages = {30--41},
    number = {1},
    month = {Oct},
    abstract = {Narrative discourse is an essential component of day-to-day communication,
    but little is known about narrative in Lewy body spectrum disorder
    (LBSD), including Parkinson's disease (PD), Parkinson's disease with
    dementia (PDD), and dementia with Lewy bodies (DLB). We performed
    a detailed analysis of a semi-structured speech sample in 32 non-aphasic
    patients with LBSD, and we related their narrative impairments to
    gray matter (GM) atrophy using voxel-based morphometry. We found
    that patients with PDD and DLB have significant difficulty organizing
    their narrative speech. This was correlated with deficits on measures
    of executive functioning and speech fluency. Regression analyses
    associated this deficit with reduced cortical volume in inferior
    frontal and anterior cingulate regions. These findings are consistent
    with a model of narrative discourse that includes executive as well
    as language components and with an impairment of the organizational
    component of narrative discourse in patients with PDD and DLB.},
    doi = {10.1016/j.bandl.2011.05.006},
    institution = {{D}epartment of {N}eurology, {U}niversity of {P}ennsylvania {S}chool
    of {M}edicine, {P}hiladelphia, {PA} 19104-4283, {USA}. ash@babel.ling.upenn.edu},
    keywords = {Aged; Atrophy, complications/pathology; Brain Mapping; Brain, pathology;
    Female; Humans; Lewy Body Disease, complications/pathology; Magnetic
    Resonance Imaging; Male; Narration; Neuropsychological Tests; Speech;
    Speech Disorders, etiology/pathology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0093-934X(11)00106-4},
    pmid = {21689852},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.bandl.2011.05.006}
    }
  • [DOI] M. Ashtari, B. Avants, L. Cyckowski, K. L. Cervellione, D. Roofeh, P. Cook, J. Gee, S. Sevy, and S. Kumra, “Medial temporal structures and memory functions in adolescents with heavy cannabis use.,” J Psychiatr Res, vol. 45, iss. 8, pp. 1055-1066, 2011.
    [Bibtex]
    @ARTICLE{Ashtari2011JPR,
    author = {Ashtari, Manzar and Avants, Brian and Cyckowski, Laura and Cervellione,
    Kelly L. and Roofeh, David and Cook, Philip and Gee, James and Sevy,
    Serge and Kumra, Sanjiv},
    title = {{M}edial temporal structures and memory functions in adolescents
    with heavy cannabis use.},
    journal = {{J} {P}sychiatr {R}es},
    year = {2011},
    volume = {45},
    pages = {1055--1066},
    number = {8},
    month = {Aug},
    abstract = {Converging lines of evidence suggest an adverse effect of heavy cannabis
    use on adolescent brain development, particularly on the hippocampus.
    In this preliminary study, we compared hippocampal morphology in
    14 "treatment-seeking" adolescents (aged 18-20) with a history of
    prior heavy cannabis use (5.8 joints/day) after an average of 6.7
    months of drug abstinence, and 14 demographically matched normal
    controls. Participants underwent a high-resolution 3D MRI as well
    as cognitive testing including the California Verbal Learning Test
    (CVLT). Heavy-cannabis users showed significantly smaller volumes
    of the right (p < 0.04) and left (p < 0.02) hippocampus, but no significant
    differences in the amygdala region compared to controls. In controls,
    larger hippocampus volumes were observed to be significantly correlated
    with higher CVLT verbal learning and memory scores, but these relationships
    were not observed in cannabis users. In cannabis users, a smaller
    right hippocampus volume was correlated with a higher amount of cannabis
    use (r = -0.57, p < 0.03). These data support a hypothesis that heavy
    cannabis use may have an adverse effect on hippocampus development.
    These findings, after an average 6.7 month of supervised abstinence,
    lend support to a theory that cannabis use may impart long-term structural
    and functional damage. Alternatively, the observed hippocampal volumetric
    abnormalities may represent a risk factor for cannabis dependence.
    These data have potential significance for understanding the observed
    relationship between early cannabis exposure during adolescence and
    subsequent development of adult psychopathology reported in the literature
    for schizophrenia and related psychotic disorders.},
    doi = {10.1016/j.jpsychires.2011.01.004},
    institution = {{D}epartment of {R}adiology, {C}hildren's {H}ospital of {P}hiladelphia,
    {P}hiladelphia, {PA} 19102, {USA}.},
    keywords = {Adolescent; Analysis of Variance; Brain Mapping; Child; Female; Humans;
    Imaging, Three-Dimensional, methods; Linear Models; Magnetic Resonance
    Imaging, methods; Male; Marijuana Abuse, complications/pathology;
    Memory Disorders, diagnosis/etiology; Neuropsychological Tests; Temporal
    Lobe, pathology; Verbal Learning, physiology; Young Adult},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S0022-3956(11)00005-7},
    pmid = {21296361},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.jpsychires.2011.01.004}
    }
  • [DOI] B. B. Avants, N. J. Tustison, G. Song, P. A. Cook, A. Klein, and J. C. Gee, “A reproducible evaluation of ANTs similarity metric performance in brain image registration.,” Neuroimage, vol. 54, iss. 3, pp. 2033-2044, 2011.
    [Bibtex]
    @ARTICLE{Avants2011Na,
    author = {Avants, Brian B. and Tustison, Nicholas J. and Song, Gang and Cook,
    Philip A. and Klein, Arno and Gee, James C.},
    title = {{A} reproducible evaluation of {ANT}s similarity metric performance
    in brain image registration.},
    journal = {{N}euroimage},
    year = {2011},
    volume = {54},
    pages = {2033--2044},
    number = {3},
    month = {Feb},
    abstract = {The United States National Institutes of Health (NIH) commit significant
    support to open-source data and software resources in order to foment
    reproducibility in the biomedical imaging sciences. Here, we report
    and evaluate a recent product of this commitment: Advanced Neuroimaging
    Tools (ANTs), which is approaching its 2.0 release. The ANTs open
    source software library consists of a suite of state-of-the-art image
    registration, segmentation and template building tools for quantitative
    morphometric analysis. In this work, we use ANTs to quantify, for
    the first time, the impact of similarity metrics on the affine and
    deformable components of a template-based normalization study. We
    detail the ANTs implementation of three similarity metrics: squared
    intensity difference, a new and faster cross-correlation, and voxel-wise
    mutual information. We then use two-fold cross-validation to compare
    their performance on openly available, manually labeled, T1-weighted
    MRI brain image data of 40 subjects (UCLA's LPBA40 dataset). We report
    evaluation results on cortical and whole brain labels for both the
    affine and deformable components of the registration. Results indicate
    that the best ANTs methods are competitive with existing brain extraction
    results (Jaccard=0.958) and cortical labeling approaches. Mutual
    information affine mapping combined with cross-correlation diffeomorphic
    mapping gave the best cortical labeling results (Jaccard=0.669±0.022).
    Furthermore, our two-fold cross-validation allows us to quantify
    the similarity of templates derived from different subgroups. Our
    open code, data and evaluation scripts set performance benchmark
    parameters for this state-of-the-art toolkit. This is the first study
    to use a consistent transformation framework to provide a reproducible
    evaluation of the isolated effect of the similarity metric on optimal
    template construction and brain labeling.},
    doi = {10.1016/j.neuroimage.2010.09.025},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {PA} 19104, {USA}. avants@grasp.cis.upenn.edu},
    keywords = {Algorithms; Brain, anatomy /&/ histology; Databases, Factual; Diagnostic
    Imaging, methods; Head, anatomy /&/ histology; Humans; Image Processing,
    Computer-Assisted, methods; Linear Models; Models, Anatomic; Models,
    Neurological; Population; Reproducibility of Results; Software},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S1053-8119(10)01206-1},
    pmid = {20851191},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2010.09.025}
    }
  • [DOI] B. B. Avants, N. J. Tustison, J. Wu, P. A. Cook, and J. C. Gee, “An open source multivariate framework for n-tissue segmentation with evaluation on public data.,” Neuroinformatics, vol. 9, iss. 4, pp. 381-400, 2011.
    [Bibtex]
    @ARTICLE{Avants2011N,
    author = {Avants, Brian B. and Tustison, Nicholas J. and Wu, Jue and Cook,
    Philip A. and Gee, James C.},
    title = {{A}n open source multivariate framework for n-tissue segmentation
    with evaluation on public data.},
    journal = {{N}euroinformatics},
    year = {2011},
    volume = {9},
    pages = {381--400},
    number = {4},
    month = {Dec},
    abstract = {We introduce Atropos, an ITK-based multivariate n-class open source
    segmentation algorithm distributed with ANTs ( http://www.picsl.upenn.edu/ANTs).
    The Bayesian formulation of the segmentation problem is solved using
    the Expectation Maximization (EM) algorithm with the modeling of
    the class intensities based on either parametric or non-parametric
    finite mixtures. Atropos is capable of incorporating spatial prior
    probability maps (sparse), prior label maps and/or Markov Random
    Field (MRF) modeling. Atropos has also been efficiently implemented
    to handle large quantities of possible labelings (in the experimental
    section, we use up to 69 classes) with a minimal memory footprint.
    This work describes the technical and implementation aspects of Atropos
    and evaluates its performance on two different ground-truth datasets.
    First, we use the BrainWeb dataset from Montreal Neurological Institute
    to evaluate three-tissue segmentation performance via (1) K-means
    segmentation without use of template data; (2) MRF segmentation with
    initialization by prior probability maps derived from a group template;
    (3) Prior-based segmentation with use of spatial prior probability
    maps derived from a group template. We also evaluate Atropos performance
    by using spatial priors to drive a 69-class EM segmentation problem
    derived from the Hammers atlas from University College London. These
    evaluation studies, combined with illustrative examples that exercise
    Atropos options, demonstrate both performance and wide applicability
    of this new platform-independent open source segmentation tool.},
    doi = {10.1007/s12021-011-9109-y},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {U}niversity
    of {P}ennsylvania, 3600 {M}arket {S}treet, {S}uite 370, {P}hiladelphia,
    {PA} 19104, {USA}. stnava@gmail.com},
    keywords = {Access to Information; Algorithms; Bayes Theorem; Databases, Factual,
    standards; Humans; Image Processing, Computer-Assisted, methods;
    Internet, standards; Magnetic Resonance Imaging, methods; Models,
    Statistical; Pattern Recognition, Automated, methods; Software, standards},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {21373993},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1007/s12021-011-9109-y}
    }
  • [DOI] S. R. Das, D. Mechanic-Hamilton, J. Pluta, M. Korczykowski, J. A. Detre, and P. A. Yushkevich, “Heterogeneity of functional activation during memory encoding across hippocampal subfields in temporal lobe epilepsy.,” Neuroimage, vol. 58, iss. 4, pp. 1121-30, 2011.
    [Bibtex]
    @ARTICLE{Das2011N,
    author = {Das, Sandhitsu R. and Mechanic-Hamilton, Dawn and Pluta, John and
    Korczykowski, Marc and Detre, John A. and Yushkevich, Paul A.},
    title = {{H}eterogeneity of functional activation during memory encoding across
    hippocampal subfields in temporal lobe epilepsy.},
    journal = {{N}euroimage},
    year = {2011},
    volume = {58},
    pages = {1121-30},
    number = {4},
    month = {7},
    abstract = {Pathology studies have shown that the anatomical subregions of the
    hippocampal formation are differentially affected in various neurological
    disorders, including temporal lobe epilepsy (TLE). Analysis of structure
    and function within these subregions using magnetic resonance imaging
    (MRI) has the potential to generate insights on disease associations
    as well as normative brain function. In this study, an atlas-based
    normalization method (Yushkevich et al., Neuroimage 44(2), 2009)
    was used to label hippocampal subregions, making it possible to examine
    subfield-level functional activation during an episodic memory task
    in two different cohorts of healthy controls and subjects diagnosed
    with intractable unilateral TLE. We report, for the first time, functional
    activation patterns within hippocampal subfields in TLE. We detected
    group differences in subfield activation between patients and controls
    as well as inter-hemispheric activation asymmetry within subfields
    in patients, with dentate gyrus (DG) and the anterior hippocampus
    region showing the greatest effects. DG was also found to be more
    active than CA1 in controls, but not in patients' epileptogenic side.
    These preliminary results will encourage further research on the
    utility of subfield-based biomarkers in TLE.},
    address = {United States},
    citation_identifier = {Das 2011},
    doi = {10.1016/j.neuroimage.2011.06.085},
    endnote_reference_number = {15},
    issn = {1095-9572},
    keywords = {Cadaver;Image Processing, Computer-Assisted;Humans;Memory;Algorithms;Atlases
    as Topic;Hippocampus;Cohort Studies;Magnetic Resonance Imaging;Epilepsy,
    Temporal Lobe;Linear Models;CA1 Region, Hippocampal;research support,
    n.i.h., extramural},
    mid = {NIHMS310882},
    organization = {Penn Image Computing and Science Laboratory (PICSL), Department of
    Radiology, University of Pennsylvania, PA, USA.},
    owner = {srdas},
    pii = {S1053-8119(11)00750-6},
    pmcid = {PMC3285462},
    publicationstatus = {Published},
    pubmedid = {21763431},
    sentelink = {file://localhost/Users/srdas/Documents/Sente/My%20Bibliographies/Das/Neuroimage/2011/Das%20Neuroimage%202011%2024135177-B3E2-4710-8088-11DCC7.pdf,Sente,PDF
    Download},
    timestamp = {2014.02.19},
    us_nlm_id = {9215515},
    uuid = {7B3370F8-8058-4ADB-BDDE-D05F2C71D635},
    web_data_source = {PubMed}
    }
  • [DOI] A. S. Jassar, C. J. Brinster, M. Vergnat, D. J. Robb, T. J. Eperjesi, A. M. Pouch, A. T. Cheung, S. J. Weiss, M. A. Acker, J. H. Gorman 3rd, R. C. Gorman, and B. Jackson, “Quantitative mitral valve modeling using real-time three-dimensional echocardiography: technique and repeatability.,” Ann Thorac Surg, vol. 91, iss. 1, pp. 165-171, 2011.
    [Bibtex]
    @ARTICLE{Jassar2011ATS,
    author = {Jassar, Arminder Singh and Brinster, Clayton J. and Vergnat, Mathieu
    and Robb, J Daniel and Eperjesi, Thomas J. and Pouch, Alison M. and
    Cheung, Albert T. and Weiss, Stuart J. and Acker, Michael A. and
    Gorman, 3rd, Joseph H and Gorman, Robert C. and Jackson, Benjamin
    M.},
    title = {{Q}uantitative mitral valve modeling using real-time three-dimensional
    echocardiography: technique and repeatability.},
    journal = {{A}nn {T}horac {S}urg},
    year = {2011},
    volume = {91},
    pages = {165--171},
    number = {1},
    month = {Jan},
    abstract = {Real-time three-dimensional (3D) echocardiography has the ability
    to construct quantitative models of the mitral valve (MV). Imaging
    and modeling algorithms rely on operator interpretation of raw images
    and may be subject to observer-dependent variability. We describe
    a comprehensive analysis technique to generate high-resolution 3D
    MV models and examine interoperator and intraoperator repeatability
    in humans.Patients with normal MVs were imaged using intraoperative
    transesophageal real-time 3D echocardiography. The annulus and leaflets
    were manually segmented using a TomTec Echo-View workstation. The
    resultant annular and leaflet point cloud was used to generate fully
    quantitative 3D MV models using custom Matlab algorithms. Eight images
    were subjected to analysis by two independent observers. Two sequential
    images were acquired for 6 patients and analyzed by the same observer.
    Each pair of annular tracings was compared with respect to conventional
    variables and by calculating the mean absolute distance between paired
    renderings. To compare leaflets, MV models were aligned so as to
    minimize their sum of squares difference, and their mean absolute
    difference was measured.Mean absolute annular and leaflet distance
    was 2.4±0.8 and 0.6±0.2 mm for the interobserver and 1.5±0.6 and
    0.5±0.2 mm for the intraobserver comparisons, respectively. There
    was less than 10\% variation in annular variables between comparisons.These
    techniques generate high-resolution, quantitative 3D models of the
    MV and can be used consistently to image the human MV with very small
    interoperator and intraoperator variability. These data lay the framework
    for reliable and comprehensive noninvasive modeling of the normal
    and diseased MV.},
    doi = {10.1016/j.athoracsur.2010.10.034},
    institution = {{D}epartment of {S}urgery, {H}ospital of the {U}niversity of {P}ennsylvania,
    {P}hiladelphia, {P}ennsylvania 19104, {USA}.},
    keywords = {Echocardiography, Three-Dimensional; Echocardiography, Transesophageal;
    Heart Valve Diseases, pathology/ultrasonography; Humans; Image Processing,
    Computer-Assisted, methods; Mitral Valve; Models, Cardiovascular;
    Monitoring, Intraoperative; Observer Variation; Predictive Value
    of Tests; Reproducibility of Results},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S0003-4975(10)02379-9},
    pmid = {21172507},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.athoracsur.2010.10.034}
    }
  • [DOI] D. P. Nathan, C. Xu, A. M. Pouch, K. B. Chandran, B. Desjardins, J. H. Gorman 3rd, R. M. Fairman, R. C. Gorman, and B. M. Jackson, “Increased wall stress of saccular versus fusiform aneurysms of the descending thoracic aorta.,” Ann Vasc Surg, vol. 25, iss. 8, pp. 1129-1137, 2011.
    [Bibtex]
    @ARTICLE{Nathan2011AVS,
    author = {Nathan, Derek P. and Xu, Chun and Pouch, Alison M. and Chandran,
    Krishnan B. and Desjardins, Benoit and Gorman, 3rd, Joseph H and
    Fairman, Ron M. and Gorman, Robert C. and Jackson, Benjamin M.},
    title = {{I}ncreased wall stress of saccular versus fusiform aneurysms of
    the descending thoracic aorta.},
    journal = {{A}nn {V}asc {S}urg},
    year = {2011},
    volume = {25},
    pages = {1129--1137},
    number = {8},
    month = {Nov},
    abstract = {Repair of fusiform descending thoracic aortic aneurysms (DTAs) is
    indicated when aneurysmal diameter exceeds a certain threshold; however,
    diameter-related indications for repair of saccular DTA are less
    well established.Human subjects with fusiform (n = 17) and saccular
    (n = 17) DTAs who underwent computed tomographic angiography were
    identified. Patients with aneurysms related to connective tissue
    disease were excluded. The thoracic aorta was segmented, reconstructed,
    and triangulated to create a mesh. Finite element analysis was performed
    using a pressure load of 120 mm Hg and a uniform aortic wall thickness
    of 3.2 mm to compare the pressure-induced wall stress of fusiform
    and saccular DTAs.The mean maximum diameter of the fusiform DTAs
    (6.0 ± 1.5 cm) was significantly greater (p = 0.006) than that of
    the saccular DTAs (4.4 ± 1.8 cm). However, mean peak wall stress
    of the fusiform DTAs (0.33 ± 0.15 MPa) was equivalent to that of
    the saccular DTAs (0.30 ± 0.14 MPa), as found by using an equivalence
    threshold of 0.15 MPa. The mean normalized wall stress (peak wall
    stress divided by maximum aneurysm radius) of the saccular DTAs was
    greater than that of the fusiform DTAs (0.16 ± 0.09 MPa/cm vs. 0.11
    ± 0.03 MPa/cm, p = 0.035).The normalized wall stress for saccular
    DTA is greater than that for fusiform DTA, indicating that geometric
    factors such as aneurysm shape influence wall stress. These results
    suggest that saccular aneurysms may be more prone to rupture than
    fusiform aneurysms of similar diameter, provide a theoretical rationale
    for the repair of saccular DTAs at a smaller diameter, and suggest
    investigation of the role of biomechanical modeling in surgical decision
    making is warranted.},
    doi = {10.1016/j.avsg.2011.07.008},
    institution = {{D}epartment of {G}eneral {S}urgery, {H}ospital of the {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {PA} 19104, {USA}.},
    keywords = {Aged; Aged, 80 and over; Aorta, Thoracic, physiopathology/radiography;
    Aortic Aneurysm, Thoracic, physiopathology/radiography; Aortography,
    methods; Biomechanical Phenomena; Blood Pressure; Chi-Square Distribution;
    Computer Simulation; Female; Finite Element Analysis; Hemodynamics;
    Humans; Male; Middle Aged; Models, Cardiovascular; Philadelphia;
    Prognosis; Retrospective Studies; Stress, Mechanical; Tomography,
    X-Ray Computed},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S0890-5096(11)00359-1},
    pmid = {22023944},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.avsg.2011.07.008}
    }
  • [DOI] A. Ramirez-Manzanares, P. A. Cook, M. Hall, M. Ashtari, and J. C. Gee, “Resolving axon fiber crossings at clinical b-values: an evaluation study.,” Med Phys, vol. 38, iss. 9, pp. 5239-5253, 2011.
    [Bibtex]
    @ARTICLE{Ramirez-Manzanares2011MP,
    author = {Ramirez-Manzanares, Alonso and Cook, Philip A. and Hall, Matt and
    Ashtari, Manzar and Gee, James C.},
    title = {{R}esolving axon fiber crossings at clinical b-values: an evaluation
    study.},
    journal = {{M}ed {P}hys},
    year = {2011},
    volume = {38},
    pages = {5239--5253},
    number = {9},
    month = {Sep},
    abstract = {Diffusion tensor magnetic resonance imaging is widely used to study
    the structure of the fiber pathways of brain white matter. However,
    the diffusion tensor cannot capture complex intravoxel fiber architecture
    such as fiber crossings of bifurcations. Consequently, a number of
    methods have been proposed to recover intravoxel fiber bundle orientations
    from high angular resolution diffusion imaging scans, optimized to
    resolve fiber crossings. It is important to improve the brain tractography
    by applying these multifiber methods to diffusion tensor protocols
    with a clinical b- value (low), which are optimized on computing
    tensor scalar statistics. In order to characterize the variance among
    different methods, consequently to be able to select the most appropriate
    one for a particular application, it is desirable to compare them
    under identical experimental conditions.In this work, the authors
    study how QBall, spherical deconvolution, persistent angular structure,
    stick and ball, diffusion basis functions, and analytical QBall methods
    perform under clinically-realistic scanning conditions, where the
    b-value is typically lower (around 1000 s∕mm(2)), and the number
    of diffusion encoding orientations is fewer (30-60) than in dedicated
    high angular resolution diffusion imaging scans. To characterize
    the performance of the methods, they consider the accuracy of the
    estimated number of fibers, the relative contribution of each fiber
    population to the total magnetic resonance signal, and the recovered
    orientation error for each fiber bundle. To this aim, they use four
    different sources of data: synthetic data from Gaussian mixture model,
    cylinder restricted model, and in vivo data from two different acquisition
    schemes.Results of their experiments indicate that: (a) it is feasible
    to apply only a subset of these methods to clinical data sets and
    (b) it allows one to characterize the performance of each method.
    In particular, two methods are not feasible to the kind of magnetic
    resonance diffusion data they test. By the characterization of their
    systematic behavior, among other conclusions, they report the method
    which better performs for the estimation of the number of diffusion
    peaks per voxel, also the method which better estimates the diffusion
    orientation.The framework they propose for comparison allows one
    to effectively characterize and compare the performance of the most
    frequently used multifiber algorithms under realistic medical settings
    and realistic signal-to-noise ratio environments. The framework is
    based on several crossings with a non-orientational bias and different
    signal models. The results they present are relevant for medical
    doctors and researchers, interested in the use of the multifiber
    solution for tractography.},
    doi = {10.1118/1.3626571},
    institution = {{D}epartment of {M}athematics, {U}niversity of {G}uanajuato, {M}ineral
    de {V}alenciana {G}uanajuato, {M}exico. alram@cimat.mx},
    keywords = {Axons, metabolism; Brain, cytology; Diffusion; Humans; Magnetic Resonance
    Imaging, methods; Models, Biological},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {21978068},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1118/1.3626571}
    }
  • [DOI] M. Vergnat, A. S. Jassar, B. M. Jackson, L. P. Ryan, T. J. Eperjesi, A. M. Pouch, S. J. Weiss, A. T. Cheung, M. A. Acker, J. H. Gorman 3rd, and R. C. Gorman, “Ischemic mitral regurgitation: a quantitative three-dimensional echocardiographic analysis.,” Ann Thorac Surg, vol. 91, iss. 1, pp. 157-164, 2011.
    [Bibtex]
    @ARTICLE{Vergnat2011ATS,
    author = {Vergnat, Mathieu and Jassar, Arminder S. and Jackson, Benjamin M.
    and Ryan, Liam P. and Eperjesi, Thomas J. and Pouch, Alison M. and
    Weiss, Stuart J. and Cheung, Albert T. and Acker, Michael A. and
    Gorman, 3rd, Joseph H and Gorman, Robert C.},
    title = {{I}schemic mitral regurgitation: a quantitative three-dimensional
    echocardiographic analysis.},
    journal = {{A}nn {T}horac {S}urg},
    year = {2011},
    volume = {91},
    pages = {157--164},
    number = {1},
    month = {Jan},
    abstract = {A comprehensive three-dimensional echocardiography based approach
    is applied to preoperative mitral valve (MV) analysis in patients
    with ischemic mitral regurgitation (IMR). This method is used to
    characterize the heterogeneous nature of the pathologic anatomy associated
    with IMR.Intraoperative real-time three-dimensional transesophageal
    echocardiograms of 18 patients with IMR (10 with anterior, 8 with
    inferior infarcts) and 17 patients with normal MV were analyzed.
    A customized image analysis protocol was used to assess global and
    regional determinants of annular size and shape, leaflet tethering
    and curvature, relative papillary muscle anatomy, and anatomic regurgitant
    orifice area.Both mitral annular area and MV tenting volume were
    increased in the IMR group as compared with patients with normal
    MV (mitral annular area=1,065±59 mm2 versus 779±44 mm2, p=0.001;
    and MV tenting volume=3,413±403 mm3 versus 1,696±200 mm3, p=0.001,
    respectively). Within the IMR group, patients with anterior infarct
    had larger annuli (1,168±99 mm2) and greater tenting volumes (4,260±779
    mm3 versus 2,735±245 mm3, p=0.06) than the inferior infarct subgroup.
    Papillary-annular distance was increased in the IMR group relative
    to normal; these distances were largest in patients with anterior
    infarcts. Whereas patients with normal MV had very consistent anatomic
    determinants, annular shape and leaflet tenting distribution in the
    IMR group were exceedingly variable. Mean anatomic regurgitant orifice
    area was 25.8±3.0 mm2, and the number of discrete regurgitant orifices
    varied from 1 to 4.Application of custom analysis techniques to three-dimensional
    echocardiography images allows a quantitative and systematic analysis
    of the MV, and demonstrates the extreme variability in pathologic
    anatomy that occurs in patients with severe IMR.},
    doi = {10.1016/j.athoracsur.2010.09.078},
    institution = {{D}epartment of {S}urgery, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {P}ennsylvania, {USA}.},
    keywords = {Aged; Aged, 80 and over; Echocardiography, Three-Dimensional; Female;
    Humans; Male; Middle Aged; Mitral Valve Insufficiency, etiology/surgery/ultrasonography;
    Myocardial Ischemia, complications/surgery/ultrasonography; Predictive
    Value of Tests; Reproducibility of Results; sisted},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S0003-4975(10)02217-4},
    pmid = {21172506},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.athoracsur.2010.09.078}
    }
  • [DOI] H. Wang, S. R. Das, J. W. Suh, M. Altinay, J. Pluta, C. Craige, B. Avants, and P. A. Yushkevich, “A Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation: Consistently Improved Performance in Hippocampus, Cortex and Brain Segmentation.,” Neuroimage, vol. 55, iss. 3, pp. 968-85, 2011.
    [Bibtex]
    @ARTICLE{Wang2011N,
    author = {Wang, Hongzhi and Das, Sandhitsu R. and Suh, Jung Wook and Altinay,
    Murat and Pluta, John and Craige, Caryne and Avants, Brian and Yushkevich,
    Paul A.},
    title = {{A} {L}earning-{B}ased {W}rapper {M}ethod to {C}orrect {S}ystematic
    {E}rrors in {A}utomatic {I}mage {S}egmentation: {C}onsistently {I}mproved
    {P}erformance in {H}ippocampus, {C}ortex and {B}rain {S}egmentation.},
    journal = {{N}euroimage},
    year = {2011},
    volume = {55},
    pages = {968-85},
    number = {3},
    month = {1},
    abstract = {We propose a simple but generally applicable approach to improving
    the accuracy of automatic image segmentation algorithms relative
    to manual segmentations. The ap- proach is based on the hypothesis
    that a large fraction of the errors produced by auto- matic segmentation
    are systematic, i.e., occur consistently from subject to subject,
    and serves as a wrapper method around a given host segmentation method.
    The wrapper method attempts to learn the intensity, spatial and contextual
    patterns associated with systematic segmentation errors produced
    by the host method on training data for which manual segmentations
    are available. The method then attempts to correct such errors in
    segmentations produced by the host method on new images. One practical
    use of the proposed wrapper method is to adapt existing segmentation
    tools, without explicit modification, to imaging data and segmentation
    protocols that are different from those on which the tools were trained
    and tuned. An open-source implementation of the proposed wrapper
    method is provided, and can be applied to a wide range of image segmentation
    problems. The wrapper method is evaluated with four host brain MRI
    segmentation methods: hippocampus segmentation using FreeSurfer (Fischl
    et al., 2002); hippocampus seg- mentation using multi-atlas label
    fusion (Artaechevarria et al., 2009); brain extraction using BET
    (Smith, 2002); and brain tissue segmentation using FAST (Zhang et
    al., 2001). The wrapper method generates 72\%, 14\%, 29\% and 21\%
    fewer erroneously segmented voxels than the respective host segmentation
    methods. In the hippocampus segmentation experiment with multi-atlas
    label fusion as the host method, the aver- age Dice overlap between
    reference segmentations and segmentations produced by the wrapper
    method is 0.908 for normal controls and 0.893 for patients with mild
    cognitive impairment. Average Dice overlaps of 0.964, 0.905 and 0.951
    are obtained for brain extraction, white matter segmentation and
    gray matter segmentation, respectively.},
    citation_identifier = {Wang 2011},
    doi = {10.1016/j.neuroimage.2011.01.006},
    endnote_reference_number = {96},
    issn = {1095-9572},
    keywords = {research support, non-u.s. gov't;Image Processing, Computer-Assisted;Humans;Middle
    Aged;Algorithms;Atlases as Topic;Brain;Databases, Factual;Female;Hippocampus;Male;Aged;Image
    Enhancement;Alzheimer Disease;Cerebral Cortex;Software;research support,
    n.i.h., extramural;Artificial Intelligence},
    mid = {NIHMS265549},
    organization = {Penn Image Computing and Science Laboratory, Departments of Radiology,
    University of Pennsylvania, Philadelphia, PA, USA.},
    owner = {srdas},
    pii = {S1053-8119(11)00024-3},
    pmcid = {PMC3049832},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {21237273},
    sentelink = {file://localhost/Users/srdas/Documents/Sente/My%20Bibliographies/Wang/Neuroimage/2011/Wang%20Neuroimage%202011%20B9172645-1992-437C-9BA4-806A0.pdf,Sente,PDF
    Download},
    timestamp = {2014.02.19},
    us_nlm_id = {9215515},
    uuid = {FA1A3150-8FFA-4DC6-9B2A-5A009FDBB67A},
    web_data_source = {PubMed}
    }
  • [DOI] H. Wang, J. W. Suh, S. Das, J. Pluta, M. Altinay, and P. Yushkevich, “Regression-Based Label Fusion for Multi-Atlas Segmentation.,” Conf Comput Vis Pattern Recognit Workshops, pp. 1113-1120, 2011.
    [Bibtex]
    @ARTICLE{Wang2011CCVPRW,
    author = {Wang, Hongzhi and Suh, Jung Wook and Das, Sandhitsu and Pluta, John
    and Altinay, Murat and Yushkevich, Paul},
    title = {{R}egression-{B}ased {L}abel {F}usion for {M}ulti-{A}tlas {S}egmentation.},
    journal = {{C}onf {C}omput {V}is {P}attern {R}ecognit {W}orkshops},
    year = {2011},
    pages = {1113-1120},
    month = {6},
    abstract = {Automatic segmentation using multi-atlas label fusion has been widely
    applied in medical image analysis. To simplify the label fusion problem,
    most methods implicitly make a strong assumption that the segmentation
    errors produced by different atlases are uncorrelated. We show that
    violating this assumption significantly reduces the efficiency of
    multi-atlas segmentation. To address this problem, we propose a regression-based
    approach for label fusion. Our experiments on segmenting the hippocampus
    in magnetic resonance images (MRI) show significant improvement over
    previous label fusion techniques},
    doi = {10.1109/CVPR.2011.5995382},
    mid = {NIHMS366473},
    owner = {srdas},
    pmcid = {PMC3343877},
    pubmedid = {22562785},
    timestamp = {2014.02.19},
    us_nlm_id = {101554644},
    uuid = {B75BDC5F-2A93-49EE-8531-49ED7A1079A6},
    web_data_source = {PubMed}
    }
  • J. Wu, S. Awate, D. Licht, B. Avants, Cedric Clouchoux, A. D. Plessis, J. Gee, and C. Limperopoulos, “Cortical Folding Measurement Is a Potential Indicator for Prenatal Brain Maturity,” in MICCAI workshop Image Analysis of Human Brain Development, Toronto, Canada, 2011.
    [Bibtex]
    @INPROCEEDINGS{Wu2011,
    author = {Jue Wu and Suyash Awate and Daniel Licht and Brian Avants and Cedric
    Clouchoux and Adre Du Plessis and James Gee and Catherine Limperopoulos},
    title = {{C}ortical {F}olding {M}easurement {I}s a {P}otential {I}ndicator
    for {P}renatal {B}rain {M}aturity},
    booktitle = {{MICCAI} workshop {I}mage {A}nalysis of {H}uman {B}rain {D}evelopment},
    year = {2011},
    address = {Toronto, Canada},
    confidential = {n},
    owner = {johnwoo},
    timestamp = {2013.05.31}
    }
  • J. Wu, K. Davis, A. Azarion, Y. Zheng, H. Wang, B. Litt, and J. C. Gee, “Brain Parcellation Aids in Electrode Localization in Epileptic Patients,” in Augmented Environments for Computer-Assisted Interventions, 2011, pp. 130-137.
    [Bibtex]
    @INPROCEEDINGS{Wu2011a,
    author = {Jue Wu and Kathryn Davis and Allan Azarion and Yuanjie Zheng and
    Hongzhi Wang and Brian Litt and James C. Gee},
    title = {{B}rain {P}arcellation {A}ids in {E}lectrode {L}ocalization in {E}pileptic
    {P}atients},
    booktitle = {{A}ugmented {E}nvironments for {C}omputer-{A}ssisted {I}nterventions},
    year = {2011},
    pages = {130-137},
    bibsource = {DBLP, http://dblp.uni-trier.de},
    ee = {http://dx.doi.org/10.1007/978-3-642-32630-1_13},
    owner = {johnwoo},
    timestamp = {2013.01.31}
    }
  • Y. Zheng, A. A. Hunter 3rd, J. Wu, H. Wang, J. Gao, M. G. Maguire, and J. C. Gee, “Landmark matching based automatic retinal image registration with linear programming and self-similarities.,” in Inf Process Med Imaging, 2011, pp. 674-685.
    [Bibtex]
    @INPROCEEDINGS{Zheng2011a,
    author = {Zheng, Yuanjie and Hunter, 3rd, Allan A and Wu, Jue and Wang, Hongzhi
    and Gao, Jianbin and Maguire, Maureen G. and Gee, James C.},
    title = {{L}andmark matching based automatic retinal image registration with
    linear programming and self-similarities.},
    booktitle = {{I}nf {P}rocess {M}ed {I}maging},
    year = {2011},
    volume = {22},
    pages = {674--685},
    abstract = {In this paper, we address the problem of landmark matching based retinal
    image registration. Two major contributions render our registration
    algorithm distinguished from many previous methods. One is a novel
    landmark-matching formulation which enables not only a joint estimation
    of the correspondences and transformation model but also the optimization
    with linear programming. The other contribution lies in the introduction
    of a reinforced self-similarities descriptor in characterizing the
    local appearance of landmarks. Theoretical analysis and a series
    of preliminary experimental results show both the effectiveness of
    our optimization scheme and the high differentiating ability of our
    features.},
    keywords = {Algorithms; Humans; Image Enhancement, methods; Image Interpretation,
    Computer-Assisted, methods; Pattern Recognition, Automated, methods;
    Programming, Linear; Reproducibility of Results; Retina, anatomy
    /&/ histology; Retinoscopy, methods; Sensitivity and Specificity;
    Subtraction Technique},
    language = {eng},
    medline-pst = {ppublish},
    owner = {johnwoo},
    pmid = {21761695},
    timestamp = {2013.01.31}
    }
  • [DOI] Y. Zheng, H. Wang, J. Wu, J. Gao, and J. C. Gee, “Multiscale analysis revisited: Detection of drusen and vessel in digital retinal images,” in Proc. IEEE Int Biomedical Imaging: From Nano to Macro Symp, 2011, pp. 689-692.
    [Bibtex]
    @INPROCEEDINGS{Zheng2011,
    author = {Yuanjie Zheng and Hongzhi Wang and Jue Wu and Jianbin Gao and Gee,
    J. C.},
    title = {{M}ultiscale analysis revisited: {D}etection of drusen and vessel
    in digital retinal images},
    booktitle = {{P}roc. {IEEE} {I}nt {B}iomedical {I}maging: {F}rom {N}ano to {M}acro
    {S}ymp},
    year = {2011},
    pages = {689--692},
    doi = {10.1109/ISBI.2011.5872500},
    owner = {johnwoo},
    timestamp = {2013.01.31},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5872500}
    }

2010 (Oral presentation)

  • C. Limperopoulos, J. Wu, D. Licht, J. C. Gee, S. P. Awate, C. Clouchoux, and A. J. du Plessis, “Quantitative MRI Measurements of Cortical Development in the Fetus,” in The 2010 Pediatric Academic Societies’ Annual Meeting, 2010 (Oral presentation).
    [Bibtex]
    @CONFERENCE{Limperopoulos2010,
    author = {Catherine Limperopoulos and Jue Wu and Daniel Licht and James C Gee
    and Suyash P Awate and Cedric Clouchoux and Adre J du Plessis},
    title = {{Q}uantitative {MRI} {M}easurements of {C}ortical {D}evelopment in
    the {F}etus},
    booktitle = {{T}he 2010 {P}ediatric {A}cademic {S}ocieties' {A}nnual {M}eeting},
    year = {2010 (Oral presentation)},
    confidential = {n},
    owner = {johnwoo},
    timestamp = {2013.05.31}
    }
  • J. Wu, S. P. Awate, D. Licht, C. Limperopoulos, and J. C. Gee, “Cortical Folding Analysis for Normal Fetuses,” in Proceedings International Society Magnetic Resonance Medicine, 2010 (Oral presentation).
    [Bibtex]
    @INPROCEEDINGS{Wu2010,
    author = {Jue Wu and Suyash P Awate and Daniel Licht and Catherine Limperopoulos
    and James C Gee},
    title = {{C}ortical {F}olding {A}nalysis for {N}ormal {F}etuses},
    booktitle = {{P}roceedings {I}nternational {S}ociety {M}agnetic {R}esonance {M}edicine},
    year = {2010 (Oral presentation)},
    note = {Oral presentation},
    confidential = {n},
    owner = {johnwoo},
    timestamp = {2013.05.31}
    }

2010

  • B. Avants, P. A. Cook, C. McMillan, M. Grossman, N. J. Tustison, Y. Zheng, and J. Gee, “Sparse unbiased analysis of anatomical variance in longitudinal imaging.,” Med Image Comput Comput Assist Interv, vol. 13, iss. Pt 1, pp. 324-331, 2010.
    [Bibtex]
    @ARTICLE{Avants2010MICCAI,
    author = {Avants, Brian and Cook, Philip A. and McMillan, Corey and Grossman,
    Murray and Tustison, Nicholas J. and Zheng, Yuanjie and Gee, James
    C.},
    title = {{S}parse unbiased analysis of anatomical variance in longitudinal
    imaging.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2010},
    volume = {13},
    pages = {324--331},
    number = {Pt 1},
    abstract = {We present a new algorithm for reliable, unbiased, multivariate longitudinal
    analysis of cortical and white matter atrophy rates with penalized
    statistical methods. The pipeline uses a step-wise approach to transform
    and personalize template information first to a single-subject template
    (SST) and then to the individual's time series data. The first stream
    of information flows from group template to the SST; the second flows
    from the SST to the individual time-points and provides unbiased,
    prior-based segmentation and measurement of cortical thickness. MRI-bias
    correction, consistent longitudinal segmentation, cortical parcellation
    and cortical thickness estimation are all based on strong use of
    the subject-specific priors built from initial diffeomorphic mapping
    between the SST and optimal group template. We evaluate our approach
    with both test-retest data and with application to a driving biological
    problem. We use test-retest data to show that this approach produces
    (a) zero change when the retest data contains the same image content
    as the test data and (b) produces normally distributed, low variance
    estimates of thickness change centered at zero when test-retest data
    is collected near in time to test data. We also show that our approach--when
    combined with sparse canonical correlation analysis--reveals plausible,
    significant, annualized decline in cortical thickness and white matter
    volume when contrasting frontotemporal dementia and normal aging.},
    institution = {{D}ept. of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA} 19104-6389 {USA}. avants@grasp.cis.upenn.edu},
    keywords = {Algorithms; Analysis of Variance; Brain Diseases, pathology; Brain,
    pathology; Humans; Image Enhancement, methods; Image Interpretation,
    Computer-Assisted, methods; Longitudinal Studies; Magnetic Resonance
    Imaging, methods; Pattern Recognition, Automated, methods; Prognosis;
    Reproducibility of Results; Sensitivity and Specificity; Subtraction
    Technique},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {20879247},
    timestamp = {2013.02.19}
    }
  • B. Avants, A. Klein, N. Tustison, J. Wu, and J. C. Gee, “Evaluation of open-access, automated brain extraction methods on multi-site multi-disorder data,” in 16th annual meeting for the Organization of Human Brain Mapping, 2010.
    [Bibtex]
    @INPROCEEDINGS{Avants2010,
    author = {Avants, B. and Klein, A. and Tustison, N. and Wu, J. and Gee, J.C.},
    title = {{E}valuation of open-access, automated brain extraction methods on
    multi-site multi-disorder data},
    booktitle = {16th annual meeting for the {O}rganization of {H}uman {B}rain {M}apping},
    year = {2010},
    owner = {johnwoo},
    timestamp = {2013.01.31},
    url = {http://www.mindboggle.info/posters/HBM2010poster_Atropos.pdf}
    }
  • [DOI] B. B. Avants, P. A. Cook, L. Ungar, J. Gee, and M. Grossman, “Dementia induces correlated reductions in white matter integrity and cortical thickness: a multivariate neuroimaging study with sparse canonical correlation analysis.,” Neuroimage, vol. 50, iss. 3, pp. 1004-1016, 2010.
    [Bibtex]
    @ARTICLE{Avants2010N,
    author = {Avants, Brian B. and Cook, Philip A. and Ungar, Lyle and Gee, James
    C. and Grossman, Murray},
    title = {{D}ementia induces correlated reductions in white matter integrity
    and cortical thickness: a multivariate neuroimaging study with sparse
    canonical correlation analysis.},
    journal = {{N}euroimage},
    year = {2010},
    volume = {50},
    pages = {1004--1016},
    number = {3},
    month = {Apr},
    abstract = {We use a new, unsupervised multivariate imaging and analysis strategy
    to identify related patterns of reduced white matter integrity, measured
    with the fractional anisotropy (FA) derived from diffusion tensor
    imaging (DTI), and decreases in cortical thickness, measured by high
    resolution T1-weighted imaging, in Alzheimer's disease (AD) and frontotemporal
    dementia (FTD). This process is based on a novel computational model
    derived from sparse canonical correlation analysis (SCCA) that allows
    us to automatically identify mutually predictive, distributed neuroanatomical
    regions from different imaging modalities. We apply the SCCA model
    to a dataset that includes 23 control subjects that are demographically
    matched to 49 subjects with autopsy or CSF-biomarker-diagnosed AD
    (n=24) and FTD (n=25) with both DTI and T1-weighted structural imaging.
    SCCA shows that the FTD-related frontal and temporal degeneration
    pattern is correlated across modalities with permutation corrected
    p<0.0005. In AD, we find significant association between cortical
    thinning and reduction in white matter integrity within a distributed
    parietal and temporal network (p<0.0005). Furthermore, we show that-within
    SCCA identified regions-significant differences exist between FTD
    and AD cortical-connective degeneration patterns. We validate these
    distinct, multimodal imaging patterns by showing unique relationships
    with cognitive measures in AD and FTD. We conclude that SCCA is a
    potentially valuable approach in image analysis that can be applied
    productively to distinguishing between neurodegenerative conditions.},
    doi = {10.1016/j.neuroimage.2010.01.041},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA} 19104-6389, {USA}. avants@grasp.cis.upenn.edu},
    keywords = {Alzheimer Disease, cerebrospinal fluid/pathology; Anisotropy; Biological
    Markers, cerebrospinal fluid; Brain, pathology; Cerebral Cortex,
    pathology; Computer Simulation; Databases, Factual; Dementia, cerebrospinal
    fluid/pathology; Diffusion Tensor Imaging, methods; Female; Frontotemporal
    Dementia, cerebrospinal fluid/pathology; Humans; Image Processing,
    Computer-Assisted, methods; Magnetic Resonance Imaging, methods;
    Male; Middle Aged; Models, Neurological; Multivariate Analysis; Nerve
    Fibers, Myelinated, pathology; Organ Size},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {S1053-8119(10)00061-3},
    pmid = {20083207},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2010.01.041}
    }
  • S. Drabycz, G. Roldán, P. de Robles, D. Adler, J. B. McIntyre, A. M. Magliocco, J. G. Cairncross, and J. R. Mitchell, “Analysis of MGMT promoter methylation status in high grade glioma patients with long term and conventional survival times: a retrospective study,” Neuroimage, vol. 49, iss. 2, 2010.
    [Bibtex]
    @ARTICLE{Drabycz2010N,
    author = {Drabycz, S. and Rold\'an, G. and de Robles, P. and Adler, D. and
    McIntyre, J. B. and Magliocco, A. M. and Cairncross, J. G. and Mitchell,
    J. R.},
    title = {{A}nalysis of {MGMT} promoter methylation status in high grade glioma
    patients with long term and conventional survival times: a retrospective
    study},
    journal = {{N}euroimage},
    year = {2010},
    volume = {49},
    number = {2},
    page = {1398--1405}
    }
  • J. T. Duda, “Characterizing connectivity in brain networks using magnetic resonance imaging,” PhD Thesis, 2010.
    [Bibtex]
    @PHDTHESIS{Duda2010Thesis,
    author = {Duda, Jeffrey T.},
    title = {{C}haracterizing connectivity in brain networks using magnetic resonance
    imaging},
    school = {University of Pennsylvania},
    year = {2010},
    owner = {jtduda},
    timestamp = {2013.06.04},
    url = {http://repository.upenn.edu/dissertations/AAI3447623/}
    }
  • J. T. Duda, C. McMillan, M. Grossman, and J. C. Gee, “Relating structural and functional connectivity to performance in a communication task.,” Med Image Comput Comput Assist Interv, vol. 13, iss. Pt 2, pp. 282-289, 2010.
    [Bibtex]
    @ARTICLE{Duda2010,
    author = {Duda, Jeffrey T. and McMillan, Corey and Grossman, Murray and Gee,
    James C.},
    title = {{R}elating structural and functional connectivity to performance
    in a communication task.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2010},
    volume = {13},
    pages = {282--289},
    number = {Pt 2},
    abstract = {Measures from event-related functional MRI, diffusion tensor imaging
    tractography and cognitive performance in a language-based task were
    used to test the hypothesis that both functional and structural connectivity
    provide independent and complementary information that aids in the
    identification of network components most related to the neurobiological
    basis for language and cognitive processing. Structural connectivity
    was measured by averaging fractional anisotropy (FA) over a geometric
    fiber bundle model that projects local white matter properties onto
    a centerline. In the uncinate fasciculus FA was found to predict
    performance on a measure of decision-making regarding homonym meaning.
    Functional synchronization of BOLD fMRI signals between frontal and
    temporal regions connected by the uncinate fasciculus was also found
    to predict the performance measure. Multiple regression analysis
    demonstrated that combining equidimensional measures of functional
    and structural connectivity identified the network components that
    most significantly predict performance.},
    institution = {{D}epartment of {B}ioengineering, {U}niversity of {P}ennsylvania,
    {USA}. jtduda@seas.upenn.edu},
    keywords = {Brain Mapping, methods; Diffusion Tensor Imaging, methods; Humans;
    Image Interpretation, Computer-Assisted, methods; Language; Magnetic
    Resonance Imaging, methods; Neural Pathways, anatomy /&/ histology/physiology;
    Task Performance and Analysis},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pmid = {20879326},
    timestamp = {2013.05.31}
    }
  • B. M. Kandel and T. E. Hullar, “The relationship of head movements to semicircular canal size in cetaceans,” The Journal of experimental biology, vol. 213, iss. 7, p. 1175–1181w, 2010.
    [Bibtex]
    @ARTICLE{Kandel2010TJoeb,
    author = {Kandel, Benjamin M and Hullar, Timothy E},
    title = {{T}he relationship of head movements to semicircular canal size in
    cetaceans},
    journal = {{T}he {J}ournal of experimental biology},
    year = {2010},
    volume = {213},
    pages = {1175--1181w},
    number = {7},
    owner = {ben},
    publisher = {The Company of Biologists Ltd},
    timestamp = {2014.03.27}
    }
  • D. J. Licht, C. Limperopoulos, A. J. Duplessis, J. C. Gee, J. Wu, G. Hedstrom, M. E. Putt, and A. Vossough, “Development of a Semiquantitative Fetal Brain Maturation Score on MRI,” in ANNALS OF NEUROLOGY, 2010, p. S88.
    [Bibtex]
    @CONFERENCE{Licht2010,
    author = {Licht, D. J. and C. Limperopoulos and A. J. Duplessis and J. C. Gee
    and J. Wu and G. Hedstrom and M. E. Putt and A. Vossough},
    title = {{D}evelopment of a {S}emiquantitative {F}etal {B}rain {M}aturation
    {S}core on {MRI}},
    booktitle = {{ANNALS} {OF} {NEUROLOGY}},
    year = {2010},
    volume = {68},
    pages = {S88},
    owner = {johnwoo},
    timestamp = {2014.02.12}
    }
  • A. M. Pouch, T. W. Cary, S. M. Schultz, and C. M. Sehgal, “In vivo noninvasive temperature measurement by B-mode ultrasound imaging.,” J Ultrasound Med, vol. 29, iss. 11, pp. 1595-1606, 2010.
    [Bibtex]
    @ARTICLE{Pouch2010JUM,
    author = {Pouch, Alison M. and Cary, Theodore W. and Schultz, Susan M. and
    Sehgal, Chandra M.},
    title = {{I}n vivo noninvasive temperature measurement by {B}-mode ultrasound
    imaging.},
    journal = {{J} {U}ltrasound {M}ed},
    year = {2010},
    volume = {29},
    pages = {1595--1606},
    number = {11},
    month = {Nov},
    abstract = {This study investigated the use of ultrasound image analysis in quantifying
    temperature changes in tissue, both ex vivo and in vivo, undergoing
    local hyperthermia.Temperature estimation is based on the thermal
    dependence of the acoustic speed in a heated medium. Because standard
    beam-forming algorithms on clinical ultrasound scanners assume a
    constant acoustic speed, temperature-induced changes in acoustic
    speed produce apparent scatterer displacements in B-mode images.
    A cross-correlation algorithm computes axial speckle pattern displacement
    in B-mode images of heated tissue, and a theoretically derived temperature-displacement
    relationship is used to generate maps of temperature changes within
    the tissue. Validation experiments were performed on excised tissue
    and in murine subjects, wherein low-intensity ultrasound was used
    to thermally treat tissue for several minutes. Diagnostic temperature
    estimation was performed using a linear array ultrasound transducer,
    while a fine-wire thermocouple invasively measured the temperature
    change.Pearson correlations ± SDs between the image-derived and thermocouple-measured
    temperature changes were R² = 0.923 ± 0.066 for 4 thermal treatments
    of excised bovine muscle tissue and R² = 0.917 ± 0.036 for 4 treatments
    of in vivo murine tumor tissue. The average differences between the
    two temperature measurements were 0.87°C ± 0.72°C for ex vivo studies
    and 0.97°C ± 0.55°C for in vivo studies. Maps of the temperature
    change distribution in tissue were generated for each experiment.This
    study demonstrates that velocimetric measurement on B-mode images
    has potential to assess temperature changes noninvasively in clinical
    applications.},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania, 3400
    {S}pruce {S}treet, {P}hiladelphia, {PA} 19104 {USA}. pouch@seas.upenn.edu},
    keywords = {Algorithms; Animals; Cattle; Female; Hyperthermia, Induced, instrumentation/methods;
    Image Processing, Computer-Assisted; Lung Neoplasms, therapy/ultrasonography;
    Mice; Mice, Nude; Temperature; Transducers; Ultrasonography, methods},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {29/11/1595},
    pmid = {20966471},
    timestamp = {2014.02.27}
    }
  • [DOI] N. J. Tustison, B. B. Avants, P. A. Cook, Y. Zheng, A. Egan, P. A. Yushkevich, and J. C. Gee, “N4ITK: improved N3 bias correction.,” IEEE Trans Med Imaging, vol. 29, iss. 6, pp. 1310-1320, 2010.
    [Bibtex]
    @ARTICLE{Tustison2010ITMI,
    author = {Tustison, Nicholas J. and Avants, Brian B. and Cook, Philip A. and
    Zheng, Yuanjie and Egan, Alexander and Yushkevich, Paul A. and Gee,
    James C.},
    title = {{N}4{ITK}: improved {N}3 bias correction.},
    journal = {{IEEE} {T}rans {M}ed {I}maging},
    year = {2010},
    volume = {29},
    pages = {1310--1320},
    number = {6},
    month = {Jun},
    abstract = {A variant of the popular nonparametric nonuniform intensity normalization
    (N3) algorithm is proposed for bias field correction. Given the superb
    performance of N3 and its public availability, it has been the subject
    of several evaluation studies. These studies have demonstrated the
    importance of certain parameters associated with the B-spline least-squares
    fitting. We propose the substitution of a recently developed fast
    and robust B-spline approximation routine and a modified hierarchical
    optimization scheme for improved bias field correction over the original
    N3 algorithm. Similar to the N3 algorithm, we also make the source
    code, testing, and technical documentation of our contribution, which
    we denote as "N4ITK," available to the public through the Insight
    Toolkit of the National Institutes of Health. Performance assessment
    is demonstrated using simulated data from the publicly available
    Brainweb database, hyperpolarized (3)He lung image data, and 9.4T
    postmortem hippocampus data.},
    doi = {10.1109/TMI.2010.2046908},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA} 19140, {USA}. ntustison@wustl.edu},
    keywords = {Algorithms; Artifacts; Brain, anatomy /&/ histology; Humans; Image
    Enhancement, methods; Image Interpretation, Computer-Assisted, methods;
    Magnetic Resonance Imaging, methods; Reproducibility of Results;
    Sensitivity and Specificity},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {20378467},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1109/TMI.2010.2046908}
    }
  • H. Wang, S. Das, J. Pluta, C. Craige, M. Altinay, B. Avants, M. Weiner, S. Mueller, and P. Yushkevich, “Standing on the shoulders of giants: improving medical image segmentation via bias correction.,” Med Image Comput Comput Assist Interv, vol. 13, iss. Pt 3, pp. 105-12, 2010.
    [Bibtex]
    @ARTICLE{Wang2010MICCAI,
    author = {Wang, Hongzhi and Das, Sandhitsu and Pluta, John and Craige, Caryne
    and Altinay, Murat and Avants, Brian and Weiner, Michael and Mueller,
    Susanne and Yushkevich, Paul},
    title = {{S}tanding on the shoulders of giants: improving medical image segmentation
    via bias correction.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2010},
    volume = {13},
    pages = {105-12},
    number = {Pt 3},
    abstract = {We propose a simple strategy to improve automatic medical image segmentation.
    The key idea is that without deep understanding of a segmentation
    method, we can still improve its performance by directly calibrating
    its results with respect to manual segmentation. We formulate the
    calibration process as a bias correction problem, which is addressed
    by machine learning using training data. We apply this methodology
    on three segmentation problems/methods and show significant improvements
    for all of them.},
    address = {Germany},
    keywords = {research support, non-u.s. gov't;Image Interpretation, Computer-Assisted;Reproducibility
    of Results;Humans;Algorithms;Brain;Sensitivity and Specificity;Magnetic
    Resonance Imaging;Image Enhancement;Pattern Recognition, Automated;research
    support, n.i.h., extramural;Artifacts},
    mid = {NIHMS279851},
    organization = {Department of Radiology, University of Pennsylvania, USA.},
    owner = {srdas},
    pmcid = {PMC3095022},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {20879389},
    timestamp = {2014.02.19},
    us_nlm_id = {101249582},
    uuid = {513A87FE-8684-4A52-8EE2-34C729F8B216},
    web_data_source = {PubMed}
    }
  • J. Wu, W. Cai, and A. C. S. Chung, “POSIT: Part-based object segmentation without intensive training,” Pattern Recognition, vol. 43, iss. 3, pp. 676-684, 2010.
    [Bibtex]
    @ARTICLE{Wu2010PR,
    author = {Jue Wu and Wenchao Cai and Albert C. S. Chung},
    title = {{POSIT}: {P}art-based object segmentation without intensive training},
    journal = {{P}attern {R}ecognition},
    year = {2010},
    volume = {43},
    pages = {676-684},
    number = {3},
    bibsource = {DBLP, http://dblp.uni-trier.de},
    ee = {http://dx.doi.org/10.1016/j.patcog.2009.07.013},
    owner = {johnwoo},
    timestamp = {2013.01.31}
    }
  • [DOI] P. A. Yushkevich, H. Wang, J. Pluta, S. Das, C. Craige, B. B. Avants, M. W. Weiner, and S. Mueller, “Nearly Automatic Segmentation of Hippocampal Subfields in In Vivo Focal T2-Weighted MRI.,” Neuroimage, vol. 53, iss. 4, pp. 1208-24, 2010.
    [Bibtex]
    @ARTICLE{Yushkevich2010N,
    author = {Yushkevich, Paul A. and Wang, Hongzhi and Pluta, John and Das, Sandhitsu
    R. and Craige, Caryne and Avants, Brian B. and Weiner, Michael W.
    and Mueller, Susanne},
    title = {{N}early {A}utomatic {S}egmentation of {H}ippocampal {S}ubfields
    in {I}n {V}ivo {F}ocal {T}2-{W}eighted {MRI}.},
    journal = {{N}euroimage},
    year = {2010},
    volume = {53},
    pages = {1208-24},
    number = {4},
    month = {6},
    abstract = {We present and evaluate a new method for automatically labeling the
    subfields of the hippocampal formation in focal 0.4x0.5x2.0mm(3)
    resolution T2-weighted magnetic resonance images that can be acquired
    in the routine clinical setting with under 5min scan time. The method
    combines multi-atlas segmentation, similarity-weighted voting, and
    a novel learning-based bias correction technique to achieve excellent
    agreement with manual segmentation. Initial partitioning of MRI slices
    into hippocampal 'head', 'body' and 'tail' slices is the only input
    required from the user, necessitated by the nature of the underlying
    segmentation protocol. Dice overlap between manual and automatic
    segmentation is above 0.87 for the larger subfields, CA1 and dentate
    gyrus, and is competitive with the best results for whole-hippocampus
    segmentation in the literature. Intraclass correlation of volume
    measurements in CA1 and dentate gyrus is above 0.89. Overlap in smaller
    hippocampal subfields is lower in magnitude (0.54 for CA2, 0.62 for
    CA3, 0.77 for subiculum and 0.79 for entorhinal cortex) but comparable
    to overlap between manual segmentations by trained human raters.
    These results support the feasibility of subfield-specific hippocampal
    morphometry in clinical studies of memory and neurodegenerative disease.},
    citation_identifier = {Yushkevich 2010},
    doi = {10.1016/j.neuroimage.2010.06.040},
    endnote_reference_number = {8},
    issn = {1095-9572},
    keywords = {research support, non-u.s. gov't;Image Interpretation, Computer-Assisted;Humans;Middle
    Aged;Algorithms;Female;Hippocampus;Male;Aged;Magnetic Resonance Imaging;Aged,
    80 and over;Adult;research support, n.i.h., extramural;Brain Mapping},
    mid = {NIHMS220223},
    organization = {Penn Image Computing and Science Laboratory, Department of Radiology,
    University of Pennsylvania, Philadelphia, USA.},
    owner = {srdas},
    pii = {S1053-8119(10)00884-0},
    pmcid = {PMC2939190},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {20600984},
    sentelink = {file://localhost/Users/srdas/Documents/Sente/My%20Bibliographies/Yushkevich/Neuroimage/2010/Yushkevich%20Neuroimage%202010%201966171D-279E-495D-A091.pdf,Manual
    Link,Local file},
    timestamp = {2014.02.19},
    us_nlm_id = {9215515},
    uuid = {4A2CD65A-FAA7-4969-8C62-4ECCBF0D6EB4},
    web_data_source = {PubMed}
    }
  • [DOI] H. Zhang, S. P. Awate, S. R. Das, J. Woo, E. R. Melhem, J. C. Gee, and P. A. Yushkevich, “A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features.,” Med Image Anal, vol. 14, iss. 5, pp. 666-73, 2010.
    [Bibtex]
    @ARTICLE{Zhang2010MIA,
    author = {Zhang, Hui and Awate, Suyash P. and Das, Sandhitsu R. and Woo, John
    H. and Melhem, Elias R. and Gee, James C. and Yushkevich, Paul A.},
    title = {{A} tract-specific framework for white matter morphometry combining
    macroscopic and microscopic tract features.},
    journal = {{M}ed {I}mage {A}nal},
    year = {2010},
    volume = {14},
    pages = {666-73},
    number = {5},
    month = {10},
    abstract = {Diffusion tensor imaging plays a key role in our understanding of
    white matter both in normal populations and in populations with brain
    disorders. Existing techniques focus primarily on using diffusivity-based
    quantities derived from diffusion tensor as surrogate measures of
    microstructural tissue properties of white matter. In this paper,
    we describe a novel tract-specific framework that enables the examination
    of white matter morphometry at both the macroscopic and microscopic
    scales. The framework leverages the skeleton-based modeling of sheet-like
    white matter fasciculi using the continuous medial representation,
    which gives a natural definition of thickness and supports its comparison
    across subjects. The thickness measure provides a macroscopic characterization
    of white matter fasciculi that complements existing analysis of microstructural
    features. The utility of the framework is demonstrated in quantifying
    white matter atrophy in Amyotrophic Lateral Sclerosis, a severe neurodegenerative
    disease of motor neurons. We show that, compared to using microscopic
    features alone, combining the macroscopic and microscopic features
    gives a more complete characterization of the disease.},
    address = {Netherlands},
    doi = {10.1016/j.media.2010.05.002},
    issn = {1361-8423},
    keywords = {Image Interpretation, Computer-Assisted;Reproducibility of Results;Amyotrophic
    Lateral Sclerosis;Humans;Algorithms;Brain;Nerve Fibers, Myelinated;Sensitivity
    and Specificity;Image Enhancement;Diffusion Tensor Imaging;Diffusion
    Magnetic Resonance Imaging;Pattern Recognition, Automated;Imaging,
    Three-Dimensional;Microscopy;research support, n.i.h., extramural},
    mid = {NIHMS208941},
    organization = {Penn Image Computing and Science Laboratory (PICSL), Department of
    Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
    garyhuizhang\@gmail.com},
    owner = {srdas},
    pii = {S1361-8415(10)00047-2},
    pmcid = {PMC2910320},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {20547469},
    timestamp = {2014.02.19},
    us_nlm_id = {9713490},
    uuid = {DD970480-F79A-4D10-AC86-D23DE8B145FF},
    web_data_source = {PubMed}
    }

2009

  • [DOI] S. R. Das, B. B. Avants, M. Grossman, and J. C. Gee, “Registration based cortical thickness measurement,” NeuroImage, vol. 45, iss. 3, pp. 867-879, 2009.
    [Bibtex]
    @ARTICLE{Das2009N,
    author = {Das, Sandhitsu R. and Avants, Brian B. and Grossman, Murray and Gee,
    James C.},
    title = {{R}egistration based cortical thickness measurement},
    journal = {{N}euro{I}mage},
    year = {2009},
    volume = {45},
    pages = {867 - 879},
    number = {3},
    abstract = {Cortical thickness is an important biomarker for image-based studies
    of the brain. A diffeomorphic registration based cortical thickness
    (DiReCT) measure is introduced where a continuous one-to-one correspondence
    between the gray matter-white matter interface and the estimated
    gray matter-cerebrospinal fluid interface is given by a diffeomorphic
    mapping in the image space. Thickness is then defined in terms of
    a distance measure between the interfaces of this sheet like structure.
    This technique also provides a natural way to compute continuous
    estimates of thickness within buried sulci by preventing opposing
    gray matter banks from intersecting. In addition, the proposed method
    incorporates neuroanatomical constraints on thickness values as part
    of the mapping process. Evaluation of this method is presented on
    synthetic images. As an application to brain images, a longitudinal
    study of thickness change in frontotemporal dementia (FTD) spectrum
    disorder is reported.},
    citation_identifier = {Das 2009a},
    doi = {10.1016/j.neuroimage.2008.12.016},
    endnote_reference_number = {168},
    issn = {1053-8119},
    keywords = {Euclidean distance;Deformable models;Cortex;Diffeomorphism;FTD;Longitudinal;Thickness},
    owner = {srdas},
    pmcid = {PMC2836782},
    primary_contributor_role = {Author},
    publicationstatus = {Unknown},
    sentelink = {{http://www.sciencedirect.com/science/article/B6WNP-4V75YSB-7/2/dfe2140dc8af0b8a3455de103f2f2340},BibTeX,Web
    page},
    timestamp = {2014.02.19},
    uuid = {8ACC4DC3-D877-44D5-A7E3-652DE51DB589}
    }
  • [DOI] S. R. Das, M. T. Lazarewicz, R. C. Wilson, and L. H. Finkel, “Sensitivity to motion features in point light displays of biological motion.,” Spat Vis, vol. 22, iss. 2, pp. 105-25, 2009.
    [Bibtex]
    @ARTICLE{Das2009SV,
    author = {Das, Sandhitsu R. and Lazarewicz, Maciej T. and Wilson, Robert C.
    and Finkel, Leif H.},
    title = {{S}ensitivity to motion features in point light displays of biological
    motion.},
    journal = {{S}pat {V}is},
    year = {2009},
    volume = {22},
    pages = {105-25},
    number = {2},
    abstract = {Psychophysical experiments are described that measure the sensitivity
    to motion features in point light displays of biological motion.
    Three motion features were investigated: the relative motion of the
    thighs, the relative motion of the thigh and leg, and the velocity
    profile of the leg. The perceptual threshold for discriminating a
    change in each motion feature was compared in upright and inverted
    point light displays. We find that subjects are more sensitive to
    two of the motion features in the upright display configuration (relative
    motion of thighs, relative motion of thigh and leg), but more sensitive
    to the third feature (velocity profile of the leg) in the inverted
    configuration. We propose that perceptual sensitivity to features
    used in biological motion perception should be greater in upright
    versus inverted displays. The results suggest that motion features
    differ in salience in biological motion perception.},
    address = {Netherlands},
    doi = {10.1163/156856809787465627},
    issn = {0169-1015},
    keywords = {Psychophysics;Humans;Female;Sensitivity and Specificity;Male;Motion
    Perception;Gait;Light;Psychomotor Performance;research support, u.s.
    gov't, non-p.h.s.},
    organization = {Department of Bioengineering, University of Pennsylvania, Philadelphia,
    PA 19104-6321, USA. sudas\@seas.upenn.edu},
    owner = {srdas},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {19228453},
    timestamp = {2014.02.19},
    us_nlm_id = {8602662},
    uuid = {0747C381-901D-4AFD-BD6C-18BBD28DDEB5},
    web_data_source = {PubMed}
    }
  • [DOI] S. R. Das, D. Mechanic-Hamilton, M. Korczykowski, J. Pluta, S. Glynn, B. B. Avants, J. A. Detre, and P. A. Yushkevich, “Structure specific analysis of the hippocampus in temporal lobe epilepsy.,” Hippocampus, vol. 19, iss. 6, pp. 517-25, 2009.
    [Bibtex]
    @ARTICLE{Das2009H,
    author = {Das, Sandhitsu R. and Mechanic-Hamilton, Dawn and Korczykowski, Marc
    and Pluta, John and Glynn, Simon and Avants, Brian B. and Detre,
    John A. and Yushkevich, Paul A.},
    title = {{S}tructure specific analysis of the hippocampus in temporal lobe
    epilepsy.},
    journal = {{H}ippocampus},
    year = {2009},
    volume = {19},
    pages = {517-25},
    number = {6},
    month = {6},
    abstract = {The hippocampus is a major structure of interest affected by temporal
    lobe epilepsy (TLE). Region of interest (ROI)-based analysis has
    traditionally been used to study hippocampal involvement in TLE,
    although spatial variation of structural and functional pathology
    have been known to exist within the ROI. In this article, structure-specific
    analysis (Yushkevich et al. (2007) Neuroimage 35:1516-1530) is applied
    to the study of both structure and function in TLE patients. This
    methodology takes into account information about the spatial correspondence
    of voxels within ROIs on left and right sides of the same subject
    as well as between subjects. Hippocampal thickness is studied as
    a measure of structural integrity, and functional activation in a
    functional magnetic resonance imaging (fMRI) experiment in which
    subjects performed a memory encoding task is studied as a measure
    of functional integrity. Pronounced disease-related decrease in thickness
    is found in posterior and anterior hippocampus. A region in the body
    also shows increased thickness in patients' healthy hippocampi compared
    with controls. Functional activation in diseased hippocampi is reduced
    in the body region compared to controls, whereas a region in the
    tail showing greater right-lateralized activation in controls also
    shows greater activation in healthy hippocampi compared with the
    diseased side in patients. Summary measurements generated by integrating
    quantities of interest over the entire hippocampus can also be used,
    as is done in conventional ROI analysis.},
    address = {United States},
    citation_identifier = {Das 2009},
    doi = {10.1002/hipo.20620},
    endnote_reference_number = {14},
    issn = {1098-1063},
    keywords = {Humans;Memory;Functional Laterality;Cluster Analysis;Hippocampus;Magnetic
    Resonance Imaging;Analysis of Variance;Epilepsy, Temporal Lobe;Signal
    Processing, Computer-Assisted;Organ Size;research support, n.i.h.,
    extramural;Neuropsychological Tests},
    mid = {NIHMS186984},
    organization = {Penn Image Computing and Science Laboratory, Department of Radiology,
    University of Pennsylvania, Philadelphia, Pennsylvania, USA. sudas\@seas.upenn.edu},
    owner = {srdas},
    pmcid = {PMC2893564},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {19437496},
    sentelink = {file://localhost/Users/srdas/Documents/Sente/My%20Bibliographies/Das/Hippocampus/2009/Das%20Hippocampus%202009%20FBF0B4A4-652B-4780-A0F3-97E1D.pdf,Manual
    Link,Local file},
    timestamp = {2014.02.19},
    us_nlm_id = {9108167},
    uuid = {9917A4B6-5D46-484C-B560-E353AA0ED514},
    web_data_source = {PubMed}
    }
  • S. R. Das, R. T. Oliver, B. B. Avants, P. D. Radoeva, D. H. Brainard, G. K. Aguirre, and J. C. Gee, Reliability of semi-automated visual area definitions in retinotopy, 2009.
    [Bibtex]
    @MISC{Das2009HBM,
    author = {Das, Sandhitsu R. and Oliver, Robyn T. and Avants, Brian B. and Radoeva,
    P. D. and Brainard, D. H. and Aguirre, Geoff K. and Gee, James C.},
    title = {{R}eliability of semi-automated visual area definitions in retinotopy},
    year = {2009},
    journal = {{H}uman {B}rain {M}apping},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {1543891F-E030-42ED-B3E9-BD075F62F2D5}
    }
  • S. R. Das, J. Pluta, B. B. Avants, H. D. Soares, and P. A. Yushkevich, Hippocampal subfield atrophy using shape based normalization: a preliminary study using the ADNI dataset, 2009.
    [Bibtex]
    @MISC{Das2009HBMa,
    author = {Das, Sandhitsu R. and Pluta, John and Avants, Brian B. and Soares,
    Holly D. and Yushkevich, Paul A.},
    title = {{H}ippocampal subfield atrophy using shape based normalization: a
    preliminary study using the {ADNI} dataset},
    year = {2009},
    journal = {{H}uman {B}rain {M}apping},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {4EE016DA-A966-405F-967A-A5202AF9970E}
    }
  • [DOI] J. Wu and A. C. S. Chung, “A novel framework for segmentation of deep brain structures based on Markov dependence tree.,” Neuroimage, vol. 46, iss. 4, pp. 1027-1036, 2009.
    [Bibtex]
    @ARTICLE{Wu2009N,
    author = {Wu, Jue and Chung, Albert C S.},
    title = {{A} novel framework for segmentation of deep brain structures based
    on {M}arkov dependence tree.},
    journal = {{N}euroimage},
    year = {2009},
    volume = {46},
    pages = {1027--1036},
    number = {4},
    month = {Jul},
    abstract = {The aim of this work is to develop a new framework for multi-object
    segmentation of deep brain structures (caudate nucleus, putamen and
    thalamus) in medical brain images. Deep brain segmentation is difficult
    and challenging because the structures of interest are of relatively
    small size and have significant shape variations. The structure boundaries
    may be blurry or even missing, and the surrounding background is
    full of irrelevant edges. To tackle these problems, we propose a
    template-based framework to fuse the information of edge features,
    region statistics and inter-structure constraints for detecting and
    locating all target brain structures such that initialization by
    hand is unnecessary. The multi-object template is organized in the
    form of a hierarchical Markov dependence tree (MDT), and multiple
    objects are efficiently matched to a target image by a top-to-down
    optimization strategy. The final segmentation is obtained through
    refinement by a B-spline based non-rigid registration between the
    exemplar image and the target image. Our approach needs only one
    example as training data. We have validated the proposed method on
    a publicly available T1-weighted magnetic resonance image database
    with expert-segmented brain structures. In the experiments, the proposed
    approach has obtained encouraging results with 0.80 Dice score for
    the caudate nuclei, 0.81 Dice score for the putamina and 0.84 Dice
    score for the thalami on average.},
    doi = {10.1016/j.neuroimage.2009.03.010},
    institution = {{B}ioengineering {P}rogram, {T}he {H}ong {K}ong {U}niversity of {S}cience
    and {T}echnology, {H}ong {K}ong.},
    keywords = {Brain Mapping, methods; Brain, anatomy /&/ histology; Humans; Image
    Interpretation, Computer-Assisted, methods; Magnetic Resonance Imaging;
    Markov Chains},
    language = {eng},
    medline-pst = {ppublish},
    owner = {johnwoo},
    pii = {S1053-8119(09)00231-6},
    pmid = {19286460},
    timestamp = {2013.01.31},
    url = {http://dx.doi.org/10.1016/j.neuroimage.2009.03.010}
    }
  • [DOI] P. A. Yushkevich, B. B. Avants, S. R. Das, J. Pluta, M. Altinay, C. Craige, and A. N. Initiative, “Bias in Estimation of Hippocampal Atrophy using Deformation-Based Morphometry Arises from Asymmetric Global Normalization: An Illustration in ADNI 3 Tesla MRI Data.,” Neuroimage, 2009.
    [Bibtex]
    @ARTICLE{Yushkevich2009N,
    author = {Yushkevich, Paul A. and Avants, Brian B. and Das, Sandhitsu R. and
    Pluta, John and Altinay, Murat and Craige, Caryne and Alzheimers
    Disease Neuroimaging Initiative},
    title = {{B}ias in {E}stimation of {H}ippocampal {A}trophy using {D}eformation-{B}ased
    {M}orphometry {A}rises from {A}symmetric {G}lobal {N}ormalization:
    {A}n {I}llustration in {ADNI} 3 {T}esla {MRI} {D}ata.},
    journal = {{N}euroimage},
    year = {2009},
    month = {12},
    abstract = {Measurement of brain change due to neurodegenerative disease and treatment
    is one of the fundamental tasks of neuroimaging. Deformation-based
    morphometry (DBM) has been long recognized as an effective and sensitive
    tool for estimating the change in the volume of brain regions over
    time. This paper demonstrates that a straightforward application
    of DBM to estimate the change in the volume of the hippocampus can
    result in substantial bias, i.e., an overestimation of the rate of
    change in hippocampal volume. In ADNI data, this bias is manifested
    as a non-zero intercept of the regression line fitted to the 6 and
    12 month rates of hippocampal atrophy. The bias is further confirmed
    by applying DBM to repeat scans of subjects acquired on the same
    day. This bias appears to be the result of asymmetry in the interpolation
    of baseline and followup images during longitudinal image registration.
    Correcting this asymmetry leads to bias-free atrophy estimation.},
    doi = {10.1016/j.neuroimage.2009.12.007},
    issn = {1095-9572},
    organization = {Penn Image Computing and Science Laboratory (PICSL), Department of
    Radiology, University of Pennsylvania, Philadelphia, PA, USA.},
    owner = {srdas},
    pii = {S1053-8119(09)01294-4},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {20005963},
    timestamp = {2014.02.19},
    us_nlm_id = {9215515},
    uuid = {C09A3BD4-9C04-4967-80B5-EE54A422187F},
    web_data_source = {PubMed}
    }
  • [DOI] P. A. Yushkevich, B. B. Avants, J. Pluta, S. Das, D. Minkoff, D. Mechanic-Hamilton, S. Glynn, S. Pickup, W. Liu, J. C. Gee, M. Grossman, and J. A. Detre, “A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T.,” Neuroimage, vol. 44, iss. 2, pp. 385-98, 2009.
    [Bibtex]
    @ARTICLE{Yushkevich2009Na,
    author = {Yushkevich, Paul A. and Avants, Brian B. and Pluta, John and Das,
    Sandhitsu and Minkoff, David and Mechanic-Hamilton, Dawn and Glynn,
    Simon and Pickup, Stephen and Liu, Weixia and Gee, James C. and Grossman,
    Murray and Detre, John A.},
    title = {{A} high-resolution computational atlas of the human hippocampus
    from postmortem magnetic resonance imaging at 9.4 {T}.},
    journal = {{N}euroimage},
    year = {2009},
    volume = {44},
    pages = {385-98},
    number = {2},
    month = {1},
    abstract = {This paper describes the construction of a computational anatomical
    atlas of the human hippocampus. The atlas is derived from high-resolution
    9.4 Tesla MRI of postmortem samples. The main subfields of the hippocampus
    (cornu ammonis fields CA1, CA2/3; the dentate gyrus; and the vestigial
    hippocampal sulcus) are labeled in the images manually using a combination
    of distinguishable image features and geometrical features. A synthetic
    average image is derived from the MRI of the samples using shape
    and intensity averaging in the diffeomorphic non-linear registration
    framework, and a consensus labeling of the template is generated.
    The agreement of the consensus labeling with manual labeling of each
    sample is measured, and the effect of aiding registration with landmarks
    and manually generated mask images is evaluated. The atlas is provided
    as an online resource with the aim of supporting subfield segmentation
    in emerging hippocampus imaging and image analysis techniques. An
    example application examining subfield-level hippocampal atrophy
    in temporal lobe epilepsy demonstrates the application of the atlas
    to in vivo studies.},
    address = {United States},
    citation_identifier = {Yushkevich 2009},
    doi = {10.1016/j.neuroimage.2008.08.042},
    endnote_reference_number = {55},
    issn = {1095-9572},
    keywords = {research support, non-u.s. gov't;Image Interpretation, Computer-Assisted;Cadaver;Reproducibility
    of Results;Humans;Algorithms;Hippocampus;Sensitivity and Specificity;Models,
    Anatomic;Magnetic Resonance Imaging;Image Enhancement;Computer Simulation;Imaging,
    Three-Dimensional;research support, n.i.h., extramural},
    mid = {NIHMS83210},
    organization = {Penn Image Computing and Science Laboratory (PICSL), Department of
    Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
    pauly2\@mail.med.upenn.edu},
    owner = {srdas},
    pii = {S1053-8119(08)00976-2},
    pmcid = {PMC2650508},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {18840532},
    sentelink = {{http://linkinghub.elsevier.com/retrieve/pii/S1053811908009762},DOI
    full text locator,Handle System resolution},
    timestamp = {2014.02.19},
    us_nlm_id = {9215515},
    uuid = {D5E5DE70-3D79-44EF-8839-7C271E78FFBF},
    web_data_source = {PubMed}
    }
  • H. Zhang, S. P. Awate, S. R. Das, J. Woo, E. R. Melhem, J. C. Gee, and P. A. Yushkevich, “A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features.,” Med Image Comput Comput Assist Interv, vol. 12, iss. Pt 2, pp. 141-9, 2009.
    [Bibtex]
    @ARTICLE{Zhang2009MICCAI,
    author = {Zhang, Hui and Awate, Suyash P. and Das, Sandhitsu R. and Woo, John
    H. and Melhem, Elias R. and Gee, James C. and Yushkevich, Paul A.},
    title = {{A} tract-specific framework for white matter morphometry combining
    macroscopic and microscopic tract features.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2009},
    volume = {12},
    pages = {141-9},
    number = {Pt 2},
    abstract = {Diffusion tensor imaging plays a key role in our understanding of
    white matter (WM) both in normal populations and in populations with
    brain disorders. Existing techniques focus primarily on using diffusivity-based
    quantities derived from diffusion tensor as surrogate measures of
    microstructural tissue properties of WM. In this paper, we describe
    a novel tract-specific framework that enables the examination of
    WM morphometry at both the macroscopic and microscopic scales. The
    framework leverages the skeleton-based modeling of sheet-like WM
    fasciculi using the continuous medial representation, which gives
    a natural definition of thickness and supports its comparison across
    subjects. The thickness measure provides a macroscopic characterization
    of WM fasciculi that complements existing analysis of microstructural
    features. The utility of the framework is demonstrated in quantifying
    WM atrophy in Amyotrophic Lateral Sclerosis, a severe neurodegenerative
    disease of motor neurons. We show that, compared to using microscopic
    features alone, combining the macroscopic and microscopic features
    gives a more holistic characterization of the disease.},
    address = {Germany},
    keywords = {Image Interpretation, Computer-Assisted;Reproducibility of Results;Humans;Algorithms;Brain;Nerve
    Fibers, Myelinated;Sensitivity and Specificity;Image Enhancement;Diffusion
    Tensor Imaging;Pattern Recognition, Automated;Imaging, Three-Dimensional;research
    support, n.i.h., extramural},
    organization = {Penn Image Computing and Science Laboratory, Department of Radiology,
    University of Pennsylvania, Philadelphia, USA.},
    owner = {srdas},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {20426106},
    timestamp = {2014.02.19},
    us_nlm_id = {101249582},
    uuid = {893C5E26-7057-4908-9888-611A109EB25B},
    web_data_source = {PubMed}
    }

2008 (Oral presentation)

  • J. Wu and A. C. S. Chung, “Markov dependence tree-based segmentation of deep brain structures.,” in Med Image Comput Comput Assist Interv, 2008 (Oral presentation), pp. 1092-1100.
    [Bibtex]
    @INPROCEEDINGS{Wu2008,
    author = {Wu, Jue and Chung, Albert C S.},
    title = {{M}arkov dependence tree-based segmentation of deep brain structures.},
    booktitle = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2008 (Oral presentation)},
    volume = {11},
    number = {2},
    pages = {1092--1100},
    abstract = {We propose a new framework for multi-object segmentation of deep brain
    structures, which have significant shape variations and relatively
    small sizes in medical brain images. In the images, the structure
    boundaries may be blurry or even missing, and the surrounding background
    is a clutter and full of irrelevant edges. We suggest a template-based
    framework, which fuses the information of edge features, region statistics
    and inter-structure constraints to detect and locate all the targeted
    brain structures such that manual initialization is unnecessary.
    The multi-object template is organized in the form of a hierarchical
    Markov dependence tree. It makes the matching of multiple objects
    efficient. Our approach needs only one example as training data and
    alleviates the demand of a large training set. The obtained segmentation
    results on real data are encouraging and the proposed method enjoys
    several important advantages over existing methods.},
    keywords = {Algorithms; Artificial Intelligence; Brain, anatomy /&/ histology;
    Humans; Image Enhancement, methods; Image Interpretation, Computer-Assisted,
    methods; Magnetic Resonance Imaging, methods; Markov Chains; Pattern
    Recognition, Automated, methods; Reproducibility of Results; Sensitivity
    and Specificity},
    language = {eng},
    medline-pst = {ppublish},
    owner = {johnwoo},
    pmid = {18982713},
    timestamp = {2013.02.01}
    }

2008

  • [DOI] B. Avants, J. T. Duda, J. Kim, H. Zhang, J. Pluta, J. C. Gee, and J. Whyte, “Multivariate analysis of structural and diffusion imaging in traumatic brain injury.,” Acad Radiol, vol. 15, iss. 11, pp. 1360-1375, 2008.
    [Bibtex]
    @ARTICLE{Avants2008,
    author = {Avants, Brian and Duda, Jeffrey T. and Kim, Junghoon and Zhang, Hui
    and Pluta, John and Gee, James C. and Whyte, John},
    title = {{M}ultivariate analysis of structural and diffusion imaging in traumatic
    brain injury.},
    journal = {{A}cad {R}adiol},
    year = {2008},
    volume = {15},
    pages = {1360--1375},
    number = {11},
    month = {Nov},
    abstract = {Diffusion tensor (DT) and T1 structural magnetic resonance images
    provide unique and complementary tools for quantifying the living
    brain. We leverage both modalities in a diffeomorphic normalization
    method that unifies analysis of clinical datasets in a consistent
    and inherently multivariate (MV) statistical framework. We use this
    technique to study MV effects of traumatic brain injury (TBI).We
    contrast T1 and DT image-based measurements in the thalamus and hippocampus
    of 12 TBI survivors and nine matched controls normalized to a combined
    DT and T1 template space. The normalization method uses maps that
    are topology-preserving and unbiased. Normalization is based on the
    full tensor of information at each voxel and, simultaneously, the
    similarity between high-resolution features derived from T1 data.
    The technique is termed symmetric normalization for MV neuroanatomy
    (SyNMN). Voxel-wise MV statistics on the local volume and mean diffusion
    are assessed with Hotelling's T(2) test with correction for multiple
    comparisons.TBI significantly (false discovery rate P < .05) reduces
    volume and increases mean diffusion at coincident locations in the
    mediodorsal thalamus and anterior hippocampus.SyNMN reveals evidence
    that TBI compromises the limbic system. This TBI morphometry study
    and an additional performance evaluation contrasting SyNMN with other
    methods suggest that the DT component may aid normalization quality.},
    doi = {10.1016/j.acra.2008.07.007},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia,
    {PA} 19104, {USA}.},
    keywords = {Adult; Brain Injuries, diagnosis; Brain, pathology; Cohort Studies;
    Diffusion Magnetic Resonance Imaging, methods; Echo-Planar Imaging,
    methods; Female; Hippocampus, pathology; Humans; Image Processing,
    Computer-Assisted, methods; Male; Middle Aged; Multivariate Analysis;
    Thalamus, pathology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pii = {S1076-6332(08)00395-4},
    pmid = {18995188},
    timestamp = {2013.05.31},
    url = {http://dx.doi.org/10.1016/j.acra.2008.07.007}
    }
  • [DOI] P. A. Cook, H. Zhang, S. P. Awate, and J. C. Gee, “Atlas-guided probabilistic diffusion-tensor fiber tractography,” in Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on, 2008, pp. 951-954.
    [Bibtex]
    @INPROCEEDINGS{Cook2008ISBI,
    author = {Cook, P.A. and Hui Zhang and Awate, S.P. and Gee, J.C.},
    title = {{A}tlas-guided probabilistic diffusion-tensor fiber tractography},
    booktitle = {{B}iomedical {I}maging: {F}rom {N}ano to {M}acro, 2008. {ISBI} 2008.
    5th {IEEE} {I}nternational {S}ymposium on},
    year = {2008},
    pages = {951-954},
    abstract = {We demonstrate the use of a diffusion tensor atlas to perform probabilistic
    tractography in diffusion tensor data. The tensors from eleven subjects
    are normalized into a common space by optimizing the similarity between
    tensors explicitly. The distribution of tensor orientations in the
    atlas space forms a prior distribution for the fiber orientation
    that is defined by the local anatomy, in contrast to previous curvature
    priors that restrict the local curvature of all tracts equally. We
    demonstrate the method in a single subject and compare tracking with
    a uniform prior, with a curvature prior, and with the atlas prior.
    The atlas information allows us to track further along the fornix
    and cingulum than the other priors.},
    doi = {10.1109/ISBI.2008.4541155},
    keywords = {biomedical MRI;brain;atlas space;cingulum;diffusion tensor atlas;diffusion-weighted
    MRI;fiber orientation;fornix;probabilistic diffusion-tensor fiber
    tractography;Anatomy;Bayesian methods;Data acquisition;Eigenvalues
    and eigenfunctions;Image reconstruction;Magnetic resonance imaging;Radiology;Streaming
    media;Tensile stress;Uncertainty;Diffusion;atlas;probabilistic tractography;tensor}
    }
  • S. R. Das, B. A. Avants, M. Grossman, and J. C. Gee, Cortical Thickness Measurements with Buried Sulcus Recovery from MRI: An Application to Dementia, 2008.
    [Bibtex]
    @MISC{Das2008AMotISfMRiM,
    author = {Das, Sandhitsu R. and Avants, Brian A. and Grossman, Murray and Gee,
    James C.},
    title = {{C}ortical {T}hickness {M}easurements with {B}uried {S}ulcus {R}ecovery
    from {MRI}: {A}n {A}pplication to {D}ementia},
    year = {2008},
    journal = {{A}nnual {M}eeting of the {I}nternational {S}ociety for {M}agnetic
    {R}esonance in {M}edicine},
    owner = {srdas},
    publicationstatus = {In Press},
    timestamp = {2014.02.19},
    uuid = {D38A2E6E-D797-4841-AC7D-3F7A847793BF}
    }
  • S. R. Das, D. Mechanic-Hamilton, M. Korczykowski, B. B. Avants, J. A. Detre, J. C. Gee, and P. A. Yushkevich, “Spatial Correspondence Based Asymmetry Analysis in fMRI,” in IEEE Symposium on Biomedical Imaging, 2008.
    [Bibtex]
    @INPROCEEDINGS{Das2008,
    author = {Das, Sandhitsu R. and Mechanic-Hamilton, Dawn and Korczykowski, Marc
    and Avants, Brian B. and Detre, John A. and Gee, James C. and Yushkevich,
    Paul A.},
    title = {{S}patial {C}orrespondence {B}ased {A}symmetry {A}nalysis in f{MRI}},
    booktitle = {{IEEE} {S}ymposium on {B}iomedical {I}maging},
    year = {2008},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {32545D32-A03C-46FA-80B2-3FDEB11C9759}
    }
  • S. R. Das, D. Mechanic-Hamilton, M. Korczykowski, B. B. Avants, J. A. Detre, J. C. Gee, and P. A. Yushkevich, Functional Asymmetry Based on Spatial Correspondence: Application to Presurgical Memory Lateralization in Epilepsy, 2008.
    [Bibtex]
    @MISC{Das2008HBM,
    author = {Das, Sandhitsu R. and Mechanic-Hamilton, Dawn and Korczykowski, Marc
    and Avants, Brian B. and Detre, John A. and Gee, James C. and Yushkevich,
    Paul A.},
    title = {{F}unctional {A}symmetry {B}ased on {S}patial {C}orrespondence: {A}pplication
    to {P}resurgical {M}emory {L}ateralization in {E}pilepsy},
    year = {2008},
    journal = {{H}uman {B}rain {M}apping},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {BF34999C-2FE4-424A-88D5-1115044B2782}
    }
  • S. R. Das, D. Mechanic-Hamilton, M. Korczykowski, J. Pluta, S. Glynn, B. B. Avants, J. A. Detre, J. C. Gee, and P. A. Yushkevich, “Spatial Correspondence Based Asymmetry Analysis in Hippocampus: Application to Temporal Lobe Epilepsy,” in Workshop on Computational Anatomy and Physiology of the Hippocampus, MICCAI 2008, 2008.
    [Bibtex]
    @INPROCEEDINGS{Das2008a,
    author = {Das, Sandhitsu R. and Mechanic-Hamilton, Dawn and Korczykowski, M.
    and Pluta, J. and Glynn, S. and Avants, B. B. and Detre, J. A. and
    Gee, J. C. and Yushkevich, P. A.},
    title = {{S}patial {C}orrespondence {B}ased {A}symmetry {A}nalysis in {H}ippocampus:
    {A}pplication to {T}emporal {L}obe {E}pilepsy},
    booktitle = {{W}orkshop on {C}omputational {A}natomy and {P}hysiology of the {H}ippocampus,
    {MICCAI} 2008},
    year = {2008},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {940FEA68-B0DD-448A-9F69-0CF4D199E4B5}
    }
  • [DOI] B. Draganski, F. Kherif, S. Klöppel, P. A. Cook, D. C. Alexander, G. J. M. Parker, R. Deichmann, J. Ashburner, and R. S. J. Frackowiak, “Evidence for segregated and integrative connectivity patterns in the human Basal Ganglia.,” J Neurosci, vol. 28, iss. 28, pp. 7143-7152, 2008.
    [Bibtex]
    @ARTICLE{Draganski2008JN,
    author = {Draganski, Bogdan and Kherif, Ferath and Klöppel, Stefan and Cook,
    Philip A. and Alexander, Daniel C. and Parker, Geoff J M. and Deichmann,
    Ralf and Ashburner, John and Frackowiak, Richard S J.},
    title = {{E}vidence for segregated and integrative connectivity patterns in
    the human {B}asal {G}anglia.},
    journal = {{J} {N}eurosci},
    year = {2008},
    volume = {28},
    pages = {7143--7152},
    number = {28},
    month = {Jul},
    abstract = {Detailed knowledge of the anatomy and connectivity pattern of cortico-basal
    ganglia circuits is essential to an understanding of abnormal cortical
    function and pathophysiology associated with a wide range of neurological
    and neuropsychiatric diseases. We aim to study the spatial extent
    and topography of human basal ganglia connectivity in vivo. Additionally,
    we explore at an anatomical level the hypothesis of coexistent segregated
    and integrative cortico-basal ganglia loops. We use probabilistic
    tractography on magnetic resonance diffusion weighted imaging data
    to segment basal ganglia and thalamus in 30 healthy subjects based
    on their cortical and subcortical projections. We introduce a novel
    method to define voxel-based connectivity profiles that allow representation
    of projections from a source to more than one target region. Using
    this method, we localize specific relay nuclei within predefined
    functional circuits. We find strong correlation between tractography-based
    basal ganglia parcellation and anatomical data from previously reported
    invasive tracing studies in nonhuman primates. Additionally, we show
    in vivo the anatomical basis of segregated loops and the extent of
    their overlap in prefrontal, premotor, and motor networks. Our findings
    in healthy humans support the notion that probabilistic diffusion
    tractography can be used to parcellate subcortical gray matter structures
    on the basis of their connectivity patterns. The coexistence of clearly
    segregated and also overlapping connections from cortical sites to
    basal ganglia subregions is a neuroanatomical correlate of both parallel
    and integrative networks within them. We believe that this method
    can be used to examine pathophysiological concepts in a number of
    basal ganglia-related disorders.},
    doi = {10.1523/JNEUROSCI.1486-08.2008},
    institution = {{W}ellcome {T}rust {C}entre for {N}euroimaging, {I}nstitute of {N}eurology,
    {UCL}, {L}ondon {WC}1{N} 3{BG}, {U}nited {K}ingdom. b.draganski@fil.ion.ucl.ac.uk},
    keywords = {Adult; Basal Ganglia, anatomy /&/ histology/physiology; Brain Mapping;
    Cerebral Cortex, anatomy /&/ histology/physiology; Female; Functional
    Laterality; Humans; Image Processing, Computer-Assisted, methods;
    Imaging, Three-Dimensional, methods; Male; Middle Aged; Neural Pathways,
    anatomy /&/ histology/physiology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {28/28/7143},
    pmid = {18614684},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1523/JNEUROSCI.1486-08.2008}
    }
  • J. Duda, B. Avants, J. Kim, H. Zhang, S. Patel, J. Whyte, and J. Gee, “Multivariate analysis of thalamo-cortical connectivity loss in TBI,” in Computer Vision and Pattern Recognition Workshops, 2008. CVPRW’08. IEEE Computer Society Conference on, 2008, pp. 1-8.
    [Bibtex]
    @INPROCEEDINGS{Duda2008,
    author = {Duda, Jeffrey and Avants, Brian and Kim, Junghoon and Zhang, Hui
    and Patel, Sunil and Whyte, John and Gee, James},
    title = {{M}ultivariate analysis of thalamo-cortical connectivity loss in
    {TBI}},
    booktitle = {{C}omputer {V}ision and {P}attern {R}ecognition {W}orkshops, 2008.
    {CVPRW}'08. {IEEE} {C}omputer {S}ociety {C}onference on},
    year = {2008},
    pages = {1--8},
    organization = {IEEE},
    owner = {jtduda},
    timestamp = {2013.05.31},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4562992}
    }
  • J. T. Duda, B. B. Avants, J. C. Asmuth, H. Zhang, M. Grossman, and J. C. Gee, “A fiber tractography based examination of neurodegeneration on language-network neuroanatomy,” in Workshop on Computational Diffusion MRI, Medical Image Computing and Computer-Assisted Intervention, 2008, pp. 191-198.
    [Bibtex]
    @INPROCEEDINGS{Duda2008a,
    author = {Duda, Jeffrey T and Avants, Brian B and Asmuth, Jane C and Zhang,
    Hui and Grossman, Murray and Gee, James C},
    title = {{A} fiber tractography based examination of neurodegeneration on
    language-network neuroanatomy},
    booktitle = {{W}orkshop on {C}omputational {D}iffusion {MRI}, {M}edical {I}mage
    {C}omputing and {C}omputer-{A}ssisted {I}ntervention},
    year = {2008},
    pages = {191--198},
    owner = {jtduda},
    timestamp = {2013.05.31}
    }
  • [DOI] S. Klöppel, B. Draganski, C. V. Golding, C. Chu, Z. Nagy, P. A. Cook, S. Hicks, C. Kennard, D. C. Alexander, G. J. M. Parker, S. J. Tabrizi, and R. S. J. Frackowiak, “White matter connections reflect changes in voluntary-guided saccades in pre-symptomatic Huntington’s disease.,” Brain, vol. 131, iss. Pt 1, pp. 196-204, 2008.
    [Bibtex]
    @ARTICLE{Kloeppel2008B,
    author = {Klöppel, Stefan and Draganski, Bogdan and Golding, Charlotte V. and
    Chu, Carlton and Nagy, Zoltan and Cook, Philip A. and Hicks, Stephen
    L. and Kennard, Christopher and Alexander, Daniel C. and Parker,
    Geoff J M. and Tabrizi, Sarah J. and Frackowiak, Richard S J.},
    title = {{W}hite matter connections reflect changes in voluntary-guided saccades
    in pre-symptomatic {H}untington's disease.},
    journal = {{B}rain},
    year = {2008},
    volume = {131},
    pages = {196--204},
    number = {Pt 1},
    month = {Jan},
    abstract = {Huntington's disease is caused by a known genetic mutation and so
    potentially can be diagnosed many years before the onset of symptoms.
    Neuropathological changes have been found in both striatum and frontal
    cortex in the pre-symptomatic stage. Disruption of cortico-striatal
    white matter fibre tracts is therefore likely to contribute to the
    first clinical signs of the disease. We analysed diffusion tensor
    MR image (DTI) data from 25 pre-symptomatic gene carriers (PSCs)
    and 20 matched controls using a multivariate support vector machine
    to identify patterns of changes in fractional anisotropy (FA). In
    addition, we performed probabilistic fibre tracking to detect changes
    in 'streamlines' connecting frontal cortex to striatum. We found
    a pattern of structural brain changes that includes putamen bilaterally
    as well as anterior parts of the corpus callosum. This pattern was
    sufficiently specific to enable us to correctly classify 82\% of
    scans as coming from a PSC or control subject. Fibre tracking revealed
    a reduction of frontal cortico-fugal streamlines reaching the body
    of the caudate in PSCs compared to controls. In the left hemispheres
    of PSCs we found a negative correlation between years to estimated
    disease onset and streamlines from frontal cortex to body of caudate.
    A large proportion of the fibres to the caudate body originate from
    the frontal eye fields, which play an important role in the control
    of voluntary saccades. This type of saccade is specifically impaired
    in PSCs and is an early clinical sign of motor abnormalities. A correlation
    analysis in 14 PSCs revealed that subjects with greater impairment
    of voluntary-guided saccades had fewer fibre tracking streamlines
    connecting the frontal cortex and caudate body. Our findings suggest
    a specific patho-physiological basis for these symptoms by indicating
    selective vulnerability of the associated white matter tracts.},
    doi = {10.1093/brain/awm275},
    institution = {{W}ellcome {T}rust {C}entre for {N}euroimaging, {I}nstitute if {N}eurology,
    {UCL}, {L}ondon, {UK}. stefan.kloeppel@uniklinik-freiburg.de},
    keywords = {Adult; Anisotropy; Brain Mapping, methods; Brain, pathology; Corpus
    Striatum, pathology; Diffusion Magnetic Resonance Imaging, methods;
    Female; Frontal Lobe, pathology; Heterozygote; Humans; Huntington
    Disease, genetics/pathology/physiopathology; Male; Middle Aged; Nerve
    Fibers, pathology; Neural Pathways, pathology; Saccades},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pii = {awm275},
    pmid = {18056161},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1093/brain/awm275}
    }
  • A. Ramirez-Manzanares, P. A. Cook, and J. C. Gee, “A comparison of methods for recovering intra-voxel white matter fiber architecture from clinical diffusion imaging scans.,” Med Image Comput Comput Assist Interv, vol. 11, iss. Pt 1, pp. 305-312, 2008.
    [Bibtex]
    @ARTICLE{Ramirez-Manzanares2008MICCAI,
    author = {Ramirez-Manzanares, Alonso and Cook, Philip A. and Gee, James C.},
    title = {{A} comparison of methods for recovering intra-voxel white matter
    fiber architecture from clinical diffusion imaging scans.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2008},
    volume = {11},
    pages = {305--312},
    number = {Pt 1},
    abstract = {Diffusion tensor magnetic resonance imaging is widely used to study
    the structure of the fiber pathways of brain white matter. However,
    the diffusion tensor cannot capture complex intra-voxel fiber architecture
    such as fiber crossings. Consequently, a number of methods have been
    proposed to recover intra-voxel fiber bundle orientations from high
    angular-resolution diffusion imaging scans, which are optimized to
    resolve fiber crossings. In this work we study how multi-tensor,
    spherical deconvolution, analytical QBall and diffusion basis function
    methods perform under clinical scanning conditions. Our experiments
    indicate that it is feasible to apply some of these methods in clinical
    data sets.},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {D}epartment
    of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia, {PA},
    {USA}. alram@mail.med.upenn.edu},
    keywords = {Algorithms; Artificial Intelligence; Diffusion Magnetic Resonance
    Imaging, methods; Humans; Image Enhancement, methods; Image Interpretation,
    Computer-Assisted, methods; Nerve Fibers, Myelinated, ultrastructure;
    Pattern Recognition, Automated, methods; Reproducibility of Results;
    Sensitivity and Specificity},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {18979761},
    timestamp = {2013.02.19}
    }
  • R. C. Wilson, S. R. Das, and L. H. Finkel, A Neural Implementation of Predictive Coding, 2008.
    [Bibtex]
    @MISC{Wilson2008CaSNC,
    author = {Wilson, Robert C. and Das, S. R. and Finkel, L. H.},
    title = {{A} {N}eural {I}mplementation of {P}redictive {C}oding},
    year = {2008},
    journal = {{C}omputational and {S}ystems {N}euroscience, {COSYNE}},
    othertype = {Proceedings of Society for Neuroscience 2004 Annual Meeting},
    owner = {srdas},
    publicationstatus = {Published},
    timestamp = {2014.02.19},
    uuid = {6A6DD05D-0349-4426-BA91-C290B94D882B}
    }

2007

  • B. Avants, J. T. Duda, H. Zhang, and J. C. Gee, “Multivariate normalization with symmetric diffeomorphisms for multivariate studies,” in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2007, Springer, 2007, pp. 359-366.
    [Bibtex]
    @INCOLLECTION{Avants2007a,
    author = {Avants, Brian and Duda, Jeffrey T and Zhang, Hui and Gee, James C},
    title = {{M}ultivariate normalization with symmetric diffeomorphisms for multivariate
    studies},
    booktitle = {{M}edical {I}mage {C}omputing and {C}omputer-{A}ssisted {I}ntervention--{MICCAI}
    2007},
    publisher = {Springer},
    year = {2007},
    pages = {359--366},
    owner = {jtduda},
    timestamp = {2013.11.13},
    url = {http://link.springer.com/chapter/10.1007/978-3-540-75757-3_44}
    }
  • B. B. Avants, J. T. Duda, H. Zhang, and J. C. Gee, “Multivariate normalization with symmetric diffeomorphisms for multivariate studies.,” Med Image Comput Comput Assist Interv, vol. 10, iss. Pt 1, pp. 359-366, 2007.
    [Bibtex]
    @ARTICLE{Avants2007,
    author = {Avants, B. B. and Duda, J. T. and Zhang, H. and Gee, J. C.},
    title = {{M}ultivariate normalization with symmetric diffeomorphisms for multivariate
    studies.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2007},
    volume = {10},
    pages = {359--366},
    number = {Pt 1},
    abstract = {Current clinical and research neuroimaging protocols acquire images
    using multiple modalities, for instance, T1, T2, diffusion tensor
    and cerebral blood flow magnetic resonance images (MRI). These multivariate
    datasets provide unique and often complementary anatomical and physiological
    information about the subject of interest. We present a method that
    uses fused multiple modality (scalar and tensor) datasets to perform
    intersubject spatial normalization. Our multivariate approach has
    the potential to eliminate inconsistencies that occur when normalization
    is performed on each modality separately. Furthermore, the multivariate
    approach uses a much richer anatomical and physiological image signature
    to infer image correspondences and perform multivariate statistical
    tests. In this initial study, we develop the theory for Multivariate
    Symmetric Normalization (MVSyN), establish its feasibility and discuss
    preliminary results on a multivariate statistical study of 22q deletion
    syndrome.},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {U}niversity
    of {P}ennsylvania, {P}hiladelphia, {PA} 19104-6389, {USA}. avants@grasp.cis.upenn.edu},
    keywords = {Adult; Algorithms; Artificial Intelligence; Brain, pathology; Demyelinating
    Diseases, diagnosis; DiGeorge Syndrome, diagnosis; Diffusion Magnetic
    Resonance Imaging, methods; Humans; Image Enhancement, methods; Image
    Interpretation, Computer-Assisted, methods; Imaging, Three-Dimensional,
    methods; Multivariate Analysis; Pattern Recognition, Automated, methods;
    Reproducibility of Results; Sensitivity and Specificity; Subtraction
    Technique},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pmid = {18051079},
    timestamp = {2013.05.31}
    }
  • T. A. Bjarnason, S. Drabycz, D. H. Adler, J. G. Cairncross, and J. R. Mitchell, “Applying the S-transform to magnetic resonance imaging texture analysis,” Fields Institute Communications, vol. 52, 2007.
    [Bibtex]
    @ARTICLE{Bjarnason2007fields,
    author = {Bjarnason, T. A. and Drabycz, S. and Adler, D. H. and Cairncross,
    J. G. and Mitchell, J. R.},
    title = {{A}pplying the {S}-transform to magnetic resonance imaging texture
    analysis},
    journal = {{F}ields {I}nstitute {C}ommunications},
    year = {2007},
    volume = {52},
    page = {311--321}
    }
  • [DOI] P. A. Cook, M. Symms, P. A. Boulby, and D. C. Alexander, “Optimal acquisition orders of diffusion-weighted MRI measurements.,” J Magn Reson Imaging, vol. 25, iss. 5, pp. 1051-1058, 2007.
    [Bibtex]
    @ARTICLE{Cook2007JMRI,
    author = {Cook, Philip A. and Symms, Mark and Boulby, Philip A. and Alexander,
    Daniel C.},
    title = {{O}ptimal acquisition orders of diffusion-weighted {MRI} measurements.},
    journal = {{J} {M}agn {R}eson {I}maging},
    year = {2007},
    volume = {25},
    pages = {1051--1058},
    number = {5},
    month = {May},
    abstract = {To propose a new method to optimize the ordering of gradient directions
    in diffusion-weighted MRI so that partial scans have the best spherical
    coverage.Diffusion-weighted MRI often uses a spherical sampling scheme,
    which acquires images sequentially with diffusion-weighting gradients
    in unique directions distributed isotropically on the hemisphere.
    If not all of the measurements can be completed, the quality of diffusion
    tensors fitted to the partial scan is sensitive to the order of the
    gradient directions in the scanner protocol. If the directions are
    in a random order, then a partial scan may cover some parts of the
    hemisphere densely but other parts sparsely and thus provide poor
    spherical coverage. We compare the results of ordering with previously
    published methods for optimizing the acquisition in simulation.Results
    show that all methods produce similar results and all improve the
    accuracy of the estimated diffusion tensors significantly over unordered
    acquisitions.The new ordering method improves the spherical coverage
    of partial scans and has the advantage of maintaining the optimal
    coverage of the complete scan.},
    doi = {10.1002/jmri.20905},
    institution = {{C}entre for {M}edical {I}mage {C}omputing, {D}epartment of {C}omputer
    {S}cience {U}niversity {C}ollege {L}ondon, {L}ondon, {UK}. p.cook@cs.ucl.ac.uk},
    keywords = {Algorithms; Anisotropy; Brain Mapping, methods; Diffusion Magnetic
    Resonance Imaging, methods; Humans; Image Enhancement, methods; Image
    Processing, Computer-Assisted},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {17457801},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1002/jmri.20905}
    }
  • S. R. Das, B. A. Avants, M. Grossman, and J. C. Gee, “Measuring Cortical Thickness Using An Image Domain Local Surface Model And Topology Preserving Segmentation,” in Mathematical Methods in Biomedical Image Analysis, 2007.
    [Bibtex]
    @INPROCEEDINGS{Das2007,
    author = {Das, Sandhitsu R. and Avants, Brian A. and Grossman, Murray and Gee,
    James C.},
    title = {{M}easuring {C}ortical {T}hickness {U}sing {A}n {I}mage {D}omain
    {L}ocal {S}urface {M}odel {A}nd {T}opology {P}reserving {S}egmentation},
    booktitle = {{M}athematical {M}ethods in {B}iomedical {I}mage {A}nalysis},
    year = {2007},
    abstract = {We present a measure of gray matter (GM) thickness based on local
    surface models in the image domain. Thickness is measured by integrating
    GM probability maps along the white matter (WM) surface normal direction.
    The method is simple to implement and allows statistical tests to
    be performed in the gray matter volume. A novel topology preserving
    segmentation method is introduced that is able to accurately recover
    GM in deep sulci. We apply this methodology to a longitudinal study
    of gray matter atrophy in a patient cohort diagnosed with frontotemporal
    dementia (FTD) spectrum disorders. Following image-based normalization
    of GM thickness maps, results show significant reduction in cortical
    thickness in several Brodmann areas spanning temporal, parietal and
    frontal lobes across subjects.},
    owner = {srdas},
    publicationstatus = {In Press},
    timestamp = {2014.02.19},
    uuid = {B6CBC7BE-FCCB-4C67-8CC2-6A1D2EEEAC74}
    }
  • S. R. Das, B. B. Avants, M. Grossman, and J. C. Gee, Longitudinal Study of Gray Matter Thickness Using Topologically Consistent Cortical Models, 2007.
    [Bibtex]
    @MISC{Das2007HBM,
    author = {Das, Sandhitsu R. and Avants, Brian B. and Grossman, Murray and Gee,
    James C.},
    title = {{L}ongitudinal {S}tudy of {G}ray {M}atter {T}hickness {U}sing {T}opologically
    {C}onsistent {C}ortical {M}odels},
    year = {2007},
    journal = {{H}um {B}rain {M}app},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {663D114F-D869-4B60-B0F7-6CC6A69896D2}
    }
  • J. T. Duda, H. Sun, G. H. Zhang, T. J. Simon, and J. C. Gee, “Fiber statistics in the corpus callosum,” in Proceedings 14th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Berlin, 2007, p. 5760.
    [Bibtex]
    @INPROCEEDINGS{Duda2007ISMRM,
    author = {Duda, Jeffrey T. and Sun, Hui and Zhang, Gary H and Simon, Tony J
    and Gee, James C.},
    title = {{F}iber statistics in the corpus callosum},
    booktitle = {{P}roceedings 14th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {B}erlin},
    year = {2007},
    pages = {5760},
    keywords = {Berlin5760}
    }
  • [DOI] J. E. Lynch, A. Pouch, R. Sanders, M. Hinders, K. Rudd, and J. Sevick, “Gaseous microemboli sizing in extracorporeal circuits using ultrasound backscatter.,” Ultrasound Med Biol, vol. 33, iss. 10, pp. 1661-1675, 2007.
    [Bibtex]
    @ARTICLE{Lynch2007UMB,
    author = {Lynch, John E. and Pouch, Alison and Sanders, Randi and Hinders,
    Mark and Rudd, Kevin and Sevick, John},
    title = {{G}aseous microemboli sizing in extracorporeal circuits using ultrasound
    backscatter.},
    journal = {{U}ltrasound {M}ed {B}iol},
    year = {2007},
    volume = {33},
    pages = {1661--1675},
    number = {10},
    month = {Oct},
    abstract = {This paper describes efforts to estimate the size of gaseous microemboli
    (GME) in extracorporeal blood circuits based on the amplitude of
    backscattered ultrasound, starting with analytic modeling of the
    scattering behavior of GME in blood. After neglecting resonance effects,
    this model predicts a linear relationship between the amplitude of
    backscattered echoes and the diameter of GME. Computer simulations
    based on the cylindrical acoustic finite integration technique were
    performed to test some of the simplifying assumptions of the analytical
    model, with the simulations predicting small deviations from the
    linear approximation that could be treated as random scatter. Ultrasonic
    and microscopic measurements of injected GME were then performed
    on a test circuit to determine the linear correlation coefficient
    between echo amplitude and GME diameter in conditions like those
    employed in real cardiopulmonary bypass (CPB) circuits. The correlation
    coefficient determined through this study was further validated in
    a closed-loop CPB circuit using canine blood. This study shows that
    the amplitude of ultrasonic backscattered echoes can be used to accurately
    estimate the size distribution of a population of detected GME when
    the spacing of emboli is great enough to minimize interference and
    other multi-path scattering effects. With the high flow rates found
    in CPB circuits, typically ranging from 2 to 6 L per minute (equivalent
    to a flow velocity of 0.3 to 1 m/s through the circuit tubing), this
    assumption will be valid even when hundreds of emboli per second
    pass through the circuit. Therefore, sizing of GME using the ultrasonic
    backscatter models described in this paper is a viable method for
    estimating embolic load delivered to a patient during a CPB procedure.},
    doi = {10.1016/j.ultrasmedbio.2007.04.008},
    institution = {{L}una {I}nnovations {I}ncorporated, {H}ampton, {VA} 23185, {USA}.
    lyncht@lunainnovations.com},
    keywords = {Algorithms; Animals; Cardiopulmonary Bypass, adverse effects; Computer
    Simulation; Dogs; Embolism, Air, ultrasonography; Extracorporeal
    Circulation, adverse effects; Humans; Image Interpretation, Computer-Assisted;
    Models, Animal; Scattering, Radiation; Ultrasonics},
    language = {eng},
    medline-pst = {ppublish},
    owner = {alison},
    pii = {S0301-5629(07)00204-9},
    pmid = {17570578},
    timestamp = {2014.02.27},
    url = {http://dx.doi.org/10.1016/j.ultrasmedbio.2007.04.008}
    }
  • [DOI] K. K. Seunarine, P. A. Cook, M. G. Hall, K. V. Embleton, G. J. M. Parker, and D. C. Alexander, “Exploiting peak anisotropy for tracking through complex structures,” in Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, 2007, pp. 1-8.
    [Bibtex]
    @INPROCEEDINGS{Seunarine2007MMBIA,
    author = {Seunarine, K.K. and Cook, P.A. and Hall, M.G. and Embleton, K.V.
    and Parker, G. J M and Alexander, D.C.},
    title = {{E}xploiting peak anisotropy for tracking through complex structures},
    booktitle = {{C}omputer {V}ision, 2007. {ICCV} 2007. {IEEE} 11th {I}nternational
    {C}onference on},
    year = {2007},
    pages = {1-8},
    abstract = {This work shows that multi-fibre reconstruction techniques, such as
    Persistent Angular Structure (PAS) MRI or QBall Imaging, provide
    much more information than just discrete fibre orientations, which
    is all that previous tractography algorithms exploit from them. We
    show that the shapes of the peaks of the functions output by multiple-fibre
    reconstruction algorithms reflect the underlying distribution of
    fibres. Furthermore, we show how to exploit this extra information
    to improve Probabilistic Index of Connectivity (PICo) tractography.
    The method uses the Bingham distribution to model the uncertainty
    in fibre-orientation estimates obtained from peaks in the PAS or
    QBall Orientation Distribution Function (ODF). The Bingham model
    captures anisotropy in the uncertainty, allowing the method to track
    through fanning and bending structures, which previous methods do
    not recover reliably. We devise a new calibration procedure to construct
    a mapping from peak shape to Bingham parameters. We test the accuracy
    of the calibration using a bootstrap experiment. Finally, we show
    that exploiting the peak shape in this way can provide improved PICo
    tractography results.},
    doi = {10.1109/ICCV.2007.4409168},
    issn = {1550-5499},
    keywords = {biomedical MRI;image reconstruction;medical image processing;probability;Bingham
    parameters;MRI;bending structures;bootstrap experiment;complex structure
    tracking;discrete fibre orientations;multifibre reconstruction;orientation
    distribution function;peak anisotropy;persistent angular structure;probabilistic
    index of connectivity;tractography algorithms;Anisotropic magnetoresistance;Biomedical
    imaging;Calibration;Diffusion tensor imaging;Image reconstruction;Magnetic
    resonance imaging;Reconstruction algorithms;Shape;Streaming media;Uncertainty},
    timestamp = {2013.04.23}
    }
  • [DOI] H. Sun, P. A. Yushkevich, H. Zhang, P. Cook, J. T. Duda, T. J. Simon, and J. C. Gee, “Shape-based normalization of the corpus callosum for DTI connectivity analysis.,” IEEE Trans Med Imaging, vol. 26, iss. 9, pp. 1166-1178, 2007.
    [Bibtex]
    @ARTICLE{Sun2007ITMI,
    author = {Sun, Hui and Yushkevich, Paul A. and Zhang, Hui and Cook, Philip
    A. and Duda, Jeffrey T. and Simon, Tony J. and Gee, James C.},
    title = {{S}hape-based normalization of the corpus callosum for {DTI} connectivity
    analysis.},
    journal = {{IEEE} {T}rans {M}ed {I}maging},
    year = {2007},
    volume = {26},
    pages = {1166--1178},
    number = {9},
    month = {Sep},
    abstract = {The continuous medial representation (cm-rep) is an approach that
    makes it possible to model, normalize, and analyze anatomical structures
    on the basis of medial geometry. Having recently presented a partial
    differential equation (PDE)-based approach for 3-D cm-rep modeling
    [1], here we present an equivalent 2-D approach that involves solving
    an ordinary differential equation. This paper derives a closed form
    solution of this equation and shows how Pythagorean hodograph curves
    can be used to express the solution as a piecewise polynomial function,
    allowing efficient and robust medial modeling. The utility of the
    approach in medical image analysis is demonstrated by applying it
    to the problem of shape-based normalization of the midsagittal section
    of the corpus callosum. Using diffusion tensor tractography, we show
    that shape-based normalization aligns subregions of the corpus callosum,
    defined by connectivity, more accurately than normalization based
    on volumetric registration. Furthermore, shape-based normalization
    helps increase the statistical power of group analysis in an experiment
    where features derived from diffusion tensor tractography are compared
    between two cohorts. These results suggest that cm-rep is an appropriate
    tool for normalizing the corpus callosum in white matter studies.},
    doi = {10.1109/TMI.2007.900322},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {D}epartment
    of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia, {PA}
    19104, {USA} . sunhui@seas.upenn.edu},
    keywords = {Agenesis of Corpus Callosum; Algorithms; Artificial Intelligence;
    Child; Computer Simulation; Corpus Callosum, pathology; Diffusion
    Magnetic Resonance Imaging, methods; Humans; Image Enhancement, methods;
    Image Interpretation, Computer-Assisted, methods; Imaging, Three-Dimensional,
    methods; Models, Neurological; Models, Statistical; Nerve Fibers,
    Myelinated, pathology; Pattern Recognition, Automated, methods; Reproducibility
    of Results; Sensitivity and Specificity; Subtraction Technique},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {17896590},
    timestamp = {2013.02.19},
    url = {http://dx.doi.org/10.1109/TMI.2007.900322}
    }
  • H. Sun, P. A. Yushkevich, H. Zhang, P. Cook, J. T. Duda, T. J. Simon, and J. C. Gee, “Evaluation of shape-based normalization in the corpus callosum for white matter connectivity analysis.,” Med Image Comput Comput Assist Interv, vol. 10, iss. Pt 2, pp. 777-784, 2007.
    [Bibtex]
    @ARTICLE{Sun2007MICCAI,
    author = {Sun, Hui and Yushkevich, Paul A. and Zhang, Hui and Cook, Philip
    A. and Duda, Jeffrey T. and Simon, Tony J. and Gee, James C.},
    title = {{E}valuation of shape-based normalization in the corpus callosum
    for white matter connectivity analysis.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2007},
    volume = {10},
    pages = {777--784},
    number = {Pt 2},
    abstract = {Recently, concerns have been raised that the correspondences computed
    by volumetric registration within homogeneous structures are primarily
    driven by regularization priors that differ among algorithms. This
    paper explores the correspondence based on geometric models for one
    of those structures, midsagittal section of the corpus callosum (MSCC),
    and compared the result with registration paradigms. We use geometric
    model called continuous medial representation (cm-rep) to normalize
    anatomical structures on the basis of medial geometry, and use features
    derived from diffusion tensor tractography for validation. We show
    that shape-based normalization aligns subregions of the MSCC, defined
    by connectivity, more accurately than normalization based on volumetric
    registration. Furthermore, shape-based normalization helps increase
    the statistical power of group analysis in an experiment where features
    derived from diffusion tensor tractography are compared between two
    cohorts. These results suggest that cm-rep is an appropriate tool
    for normalizing the MSCC in white matter studies.},
    institution = {{P}enn {I}mage {C}omputing and {S}cience {L}aboratory, {D}epartment
    of {R}adiology, {U}niversity of {P}ennsylvania, {P}hiladelphia, {USA}.},
    keywords = {Algorithms; Artificial Intelligence; Chromosome Disorders, pathology;
    Computer Simulation; Corpus Callosum, pathology; Diffusion Magnetic
    Resonance Imaging, methods; Humans; Image Interpretation, Computer-Assisted,
    methods; Imaging, Three-Dimensional, methods; Models, Neurological;
    Models, Statistical; Nerve Fibers, Myelinated, pathology; Pattern
    Recognition, Automated, methods; Reproducibility of Results; Sensitivity
    and Specificity; Subtraction Technique},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {18044639},
    timestamp = {2013.02.19}
    }
  • [DOI] J. Wu and A. C. S. Chung, “Markov Random Field Energy Minimization via Iterated Cross Entropy with Partition Strategy,” in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing ICASSP 2007, 2007.
    [Bibtex]
    @INPROCEEDINGS{Wu2007,
    author = {Jue Wu and Chung, A. C. S.},
    title = {{Markov} {R}andom {F}ield {E}nergy {M}inimization via {I}terated
    {C}ross {E}ntropy with {P}artition {S}trategy},
    booktitle = {{P}roc. {IEEE} {I}nt. {C}onf. {A}coustics, {S}peech and {S}ignal
    {P}rocessing {ICASSP} 2007},
    year = {2007},
    volume = {1},
    doi = {10.1109/ICASSP.2007.366715},
    owner = {johnwoo},
    timestamp = {2013.02.01},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4217115}
    }
  • [DOI] J. Wu and A. C. S. Chung, “A Segmentation Model Using Compound Markov Random Fields Based on a Boundary Model,” IEEE Transactions on Image Processing, vol. 16, iss. 1, pp. 241-252, 2007.
    [Bibtex]
    @ARTICLE{Wu2007IToIP,
    author = {Jue Wu and Chung, A. C. S.},
    title = {{A} {S}egmentation {M}odel {U}sing {C}ompound {Markov} {R}andom {F}ields
    {B}ased on a {B}oundary {M}odel},
    journal = {{IEEE} {T}ransactions on {I}mage {P}rocessing},
    year = {2007},
    volume = {16},
    pages = {241--252},
    number = {1},
    doi = {10.1109/TIP.2006.884933},
    owner = {johnwoo},
    timestamp = {2013.01.31},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4032831}
    }

2006

  • B. B. Avants, S. K. Lakshmikanth, J. Duda, J. A. Detre, and M. Grossman, “Robust cerebral blood flow reconstruction from perfusion imaging with an open-source, multi-platform toolkit,” in Proceedings of Perfusion MRI: Standardization, Beyond CBF and Everyday Clinical Applications, International Society for Magnetic Resonance in Medicine Scientific Workshop, Amsterdam, 2006, p. 21.
    [Bibtex]
    @INPROCEEDINGS{Avants2012ISMRMASL,
    author = {Avants, Brian B. and Lakshmikanth, Shrinidhi K. and Duda, Jeffrey
    T. and Detre, John A. and Grossman, Murray},
    title = {{R}obust cerebral blood flow reconstruction from perfusion imaging
    with an open-source, multi-platform toolkit},
    booktitle = {{P}roceedings of {P}erfusion {MRI}: {S}tandardization, {B}eyond {CBF}
    and {E}veryday {C}linical {A}pplications, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine {S}cientific {W}orkshop,
    {A}msterdam},
    year = {2006},
    pages = {21}
    }
  • [DOI] W. Cai, J. Wu, and A. C. S. Chung, “Shape-Based Image Segmentation Using Normalized Cuts,” in Proc. IEEE Int Image Processing Conf, 2006, pp. 1101-1104.
    [Bibtex]
    @INPROCEEDINGS{Cai2006,
    author = {Wenchao Cai and Jue Wu and Chung, A. C. S.},
    title = {{S}hape-{B}ased {I}mage {S}egmentation {U}sing {N}ormalized {C}uts},
    booktitle = {{P}roc. {IEEE} {I}nt {I}mage {P}rocessing {C}onf},
    year = {2006},
    pages = {1101--1104},
    doi = {10.1109/ICIP.2006.312748},
    owner = {johnwoo},
    timestamp = {2013.02.01},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4106726}
    }
  • P. A. Cook and D. C. Alexander, “Modelling uncertainty in two fibre-orientation estimates within a voxel,” in Proceedings 13th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Seattle, 2006, p. 1629.
    [Bibtex]
    @INPROCEEDINGS{Cook2006ISMRMc,
    author = {Cook, Philip A. and Alexander, Daniel C.},
    title = {{M}odelling uncertainty in two fibre-orientation estimates within
    a voxel},
    booktitle = {{P}roceedings 13th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}eattle},
    year = {2006},
    pages = {1629},
    abstract = {The Probabilistic Index of Connectivity tractography method uses Monte-Carlo
    streamline generation to create maps of connection probability. A
    probability density function (PDF) is associated with the fibre orientation
    in each voxel. We present a new model of the fibre-orientation PDF
    that models the uncertainty of two distinct fibre orientations within
    a voxel. Unlike previous work, the new model does not assume circular
    contours of the PDF on the sphere. We show an example of the model
    where a Gaussian mixture model is used to estimate the two fibre
    orientations in a simulated fibre crossing.},
    keywords = {Seattle1629}
    }
  • P. A. Cook, B. Yu, S. Nedjati-Gilani, K. K. Seunarine, M. Hall, G. J. M. Parker, and D. C. Alexander, “Camino: Open-Source Diffusion-MRI Reconstruction and Processing,” in Proceedings 13th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Seattle, 2006, p. 2759.
    [Bibtex]
    @INPROCEEDINGS{Cook2006ISMRMd,
    author = {Cook, Philip A. and Yu, Bai and Nedjati-Gilani, Shahrum and Seunarine,
    Kiran K. and Hall, Matt and Parker, Geoffrey J. M. and Alexander,
    Daniel C.},
    title = {{C}amino: {O}pen-{S}ource {D}iffusion-{MRI} {R}econstruction and
    {P}rocessing},
    booktitle = {{P}roceedings 13th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}eattle},
    year = {2006},
    pages = {2759},
    abstract = {Camino is an open-source, object-oriented software package for processing
    diffusion MRI data. Camino implements a data processing pipeline,
    which allows for easy scripting and flexible integration with other
    software. Camino implements and integrates standard and advanced
    algorithms for synthesis, reconstruction, statistical analysis and
    tractography in diffusion-MRI imaging and is freely available to
    the research community. We explain the pipeline approach to processing
    diffusion-MRI data and summarize the main features of the Camino
    toolkit.},
    keywords = {Seattle2759}
    }
  • P. Cook, P. Boulby, M. Symms, and D. Alexander, “Ordering diffusion-weighted MRI measurements improves results from partially completed scans,” in Proceedings 13th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Seattle, 2006, p. 1035.
    [Bibtex]
    @INPROCEEDINGS{Cook2006ISMRM,
    author = {Cook, P. and Boulby, P. and Symms, M. and Alexander, D.},
    title = {{O}rdering diffusion-weighted {MRI} measurements improves results
    from partially completed scans},
    booktitle = {{P}roceedings 13th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}eattle},
    year = {2006},
    pages = {1035},
    abstract = {Diffusion-MRI often uses a spherical sampling scheme, which acquires
    images sequentially with diffusion weighting gradients in unique
    directions distributed isotropically on the hemisphere. If not all
    of the measurements can be completed, the quality of results from
    the partial scan is sensitive to the order of the gradient directions
    in the scanner protocol. A partial scan may cover parts of the hemisphere
    densely but other parts sparsely and thus provide poor spherical
    coverage. We present a method to optimise maximise the spherical
    coverage of partial scans without affecting the spherical sampling
    of the complete acquisition.},
    keywords = {Seattle1035},
    timestamp = {2013.02.22}
    }
  • S. R. Das, M. T. Lazarewicz, R. C. Wilson, and L. H. Finkel, Sensitivity to motion features in upright and inverted point-light displays [Abstract], 2006.
    [Bibtex]
    @MISC{Das2006JV,
    author = {Das, S. R. and Lazarewicz, M. T. and Wilson, R. C. and Finkel, L.
    H.},
    title = {{S}ensitivity to motion features in upright and inverted point-light
    displays [{A}bstract]},
    year = {2006},
    abstract = {iological motion recognition in point-light displays exhibits a well-known
    inversion effect (Grossman and Blake, 2001; Pavlova and Sokolov,
    2000) analogous to inversion effects in other expert recognition
    systems like face recognition (Yin, 1969). We measured human observers'
    sensitivity to perturbations of intermediate level spatiotemporal
    features in point-light displays of upright and inverted walkers.
    We found that observers are more sensitive to perturbation of certain
    features in upright displays but more sensitive to other features
    in inverted displays. The features with greater sensitivity in upright
    displays describe the relative motion of adjacent limb segments (e.g.,
    left thigh/right thigh, and thigh/leg). In contrast, perturbations
    to a feature that describes the angular velocity of the limbs result
    in greater sensitivity in inverted displays. We hypothesize that
    certain intermediate level features are used by the visual system
    for biological motion recognition (Casile and Giese, 2005). Detection
    of these features may be orientation sensitive and therefore observers
    more sensitive to perturbations of these features in upright displays.
    On the other hand, if a feature is not used for recognition, the
    sensitivities may be the same under upright and inverted conditions,
    and may actually be higher in inverted displays because of greater
    impact of local attentional mechanisms in the absence of global high
    level integration. We thank the Center for Human Modeling and Simulation
    for use of the ReActor system. This research was supported by the
    DoD Multidisciplinary University Research Initiative (MURI) program
    administered by the Office of Naval Research under grant N00014-01-1-0625.},
    journal = {{J} {V}is},
    number = {6},
    owner = {srdas},
    publicationstatus = {Published},
    timestamp = {2014.02.19},
    uuid = {1D32EAD3-C2A4-4EB1-BFC8-595D1D0C1045},
    volume = {6}
    }
  • S. R. Das, R. C. Wilson, M. T. Lazarewicz, and L. H. Finkel, “Two-Stage Principal Component Analysis for Gait Recognition,” in Automatic Face and Gesture Recognition, 2006 FGR 2006 7th International Conference on, 2006, pp. 579-584.
    [Bibtex]
    @INPROCEEDINGS{Das2006,
    author = {Das, S. R. and Wilson, R. C. and Lazarewicz, M. T. and Finkel, L.
    H.},
    title = {{T}wo-{S}tage {P}rincipal {C}omponent {A}nalysis for {G}ait {R}ecognition},
    booktitle = {{A}utomatic {F}ace and {G}esture {R}ecognition, 2006 {FGR} 2006 7th
    {I}nternational {C}onference on},
    year = {2006},
    pages = {579-584},
    keywords = {eigenspace based analysis;gait classification;gait recognition;two-stage
    principal component analysis;motion;gait analysis;human gait;principal
    component analysis;image motion analysis;PCA;image classification;spatiotemporal
    motion features;gesture recognition;eigenvalues and eigenfunctions},
    notes = {(0) We describe a methodology for classification of gait (walk, run,
    jog, etc.) and recognition of individuals based on gait using two
    successive stages of principal component analysis (PCA) on kinematic
    data. In psychophysical studies, we have found that observers are
    sensitive to specific "motion features" that characterize human gait.
    These spatiotemporal motion features closely correspond to the first
    few principal components (PC) of the kinematic data. The first few
    PCs provide a representation of an individual gait as trajectory
    along a low-dimensional manifold in PC space. A second stage of PCA
    captures variability in the shape of this manifold across individuals
    or gaits. This simple eigenspace based analysis is capable of accurate
    classification across subjects.},
    owner = {srdas},
    primary_contributor_role = {Author},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {B9FF6737-98B6-42DC-BE00-2A266A0D9C86}
    }
  • S. R. Das, R. C. Wilson, M. T. Lazarewicz, and L. H. Finkel, “Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition,” Journal of Multimedia, vol. 1, iss. 5, pp. 9-17, 2006.
    [Bibtex]
    @ARTICLE{Das2006JoM,
    author = {Das, Sandhitsu R. and Wilson, Robert C. and Lazarewicz, Maciej T.
    and Finkel, Leif H.},
    title = {{T}wo-{S}tage {PCA} {E}xtracts {S}patiotemporal {F}eatures for {G}ait
    {R}ecognition},
    journal = {{J}ournal of {M}ultimedia},
    year = {2006},
    volume = {1},
    pages = {9-17},
    number = {5},
    month = {8},
    abstract = {We propose a technique for gait recognition from motion capture data
    based on two successive stages of principal component analysis (PCA)
    on kinematic data. The first stage of PCA provides a low dimensional
    representation of gait. Components of this representation closely
    correspond to particular spatiotemporal features of gait that we
    have shown to be important for visual recognition of gait in a separate
    psychophysical study. A second stage of PCA captures the shape of
    the trajectory within the low dimensional space during a given gait
    cycle across different individuals or gaits. The projection space
    of the second stage of PCA has distinguishable clusters corresponding
    to the individual identity and type of gait. Despite the simple eigen-analysis
    based approach, promising recognition performance is obtained.},
    keywords = {gait recognition;Principal Components Analysis},
    owner = {srdas},
    publicationstatus = {Published},
    publisher = {Academy Publisher},
    tags = {Principal Components Analysis;gait recognition},
    timestamp = {2014.02.19},
    uuid = {60E01491-C4A4-4FF8-9C9D-954CC9DD6F1B}
    }
  • J. T. Duda, B. B. Avants, and J. C. Gee, “A Tool for the quantitative comparison of fiber tractography,” in Proceedings 12th Annual Meeting of the Organization for Human Brain Mapping, Florence, 2006.
    [Bibtex]
    @INPROCEEDINGS{Duda2006HBMa,
    author = {Duda, Jeffrey T. and Avants, Brian B. and Gee, James C.},
    title = {{A} {T}ool for the quantitative comparison of fiber tractography},
    booktitle = {{P}roceedings 12th {A}nnual {M}eeting of the {O}rganization for {H}uman
    {B}rain {M}apping, {F}lorence},
    year = {2006}
    }
  • J. T. Duda, B. B. Avants, and J. C. Gee, “Examining tissue micro-architecture via interrogation of diffusion tensor fiber tractography,” in Proceedings 12th Annual Meeting of the Organization for Human Brain Mapping, Florence, 2006.
    [Bibtex]
    @INPROCEEDINGS{Duda2006HBMb,
    author = {Duda, Jeffrey T. and Avants, Brian B. and Gee, James C.},
    title = {{E}xamining tissue micro-architecture via interrogation of diffusion
    tensor fiber tractography},
    booktitle = {{P}roceedings 12th {A}nnual {M}eeting of the {O}rganization for {H}uman
    {B}rain {M}apping, {F}lorence},
    year = {2006}
    }
  • J. T. Duda, G. H. Zhang, T. J. Simon, and J. Gee, “Fiber tract based interrogation of white matter,” in Proceedings 13th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Seattle, 2006, p. 2745.
    [Bibtex]
    @INPROCEEDINGS{Duda2006ISMRM,
    author = {Duda, Jeffrey T. and Zhang, Gary H and Simon, Tony J and Gee, James
    C.},
    title = {{F}iber tract based interrogation of white matter},
    booktitle = {{P}roceedings 13th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}eattle},
    year = {2006},
    pages = {2745},
    keywords = {Seattle2745},
    url = {http://cds.ismrm.org/ismrm-2006/files/02745.pdf}
    }
  • L. H. Finkel, R. C. Wilson, S. R. Das, and M. T. Lazarewicz, Network Mechanisms for Biological Motion Recognition, 2006.
    [Bibtex]
    @MISC{Finkel2006AMotSfMP,
    author = {Finkel, Leif H. and Wilson, Robert C. and Das, Sandhitsu R. and Lazarewicz,
    Maciej T.},
    title = {{N}etwork {M}echanisms for {B}iological {M}otion {R}ecognition},
    year = {2006},
    journal = {{A}nnual {M}eeting of the {S}ociety for {M}athematical {P}sychology},
    owner = {srdas},
    publicationstatus = {Unknown},
    timestamp = {2014.02.19},
    uuid = {3D776A3D-2B4E-49E7-B61E-490DD2A4496C}
    }
  • J. C. Gee, H. Zhang, A. Dubb, B. B. Avants, P. A. Yushkevich, and J. T. Duda, “Anatomy-based visualizations of diffusion tensor images of brain white matter,” in Visualization and Processing of Tensor Fields, Springer, 2006, pp. 155-163.
    [Bibtex]
    @INCOLLECTION{Gee2006,
    author = {Gee, James C and Zhang, Hui and Dubb, Abraham and Avants, Brian B
    and Yushkevich, Paul A and Duda, Jeffrey T},
    title = {{A}natomy-based visualizations of diffusion tensor images of brain
    white matter},
    booktitle = {{V}isualization and {P}rocessing of {T}ensor {F}ields},
    publisher = {Springer},
    year = {2006},
    pages = {155--163},
    owner = {jtduda},
    timestamp = {2013.05.31},
    url = {http://link.springer.com/chapter/10.1007/3-540-31272-2_8}
    }
  • W. F. Teskey, D. H. Adler, and W. J. Teskey, “Determining free flight performance by surveying engineering techniques,” J Surv Eng, vol. 132, iss. 2, 2006.
    [Bibtex]
    @ARTICLE{Teskey2006jsengg,
    author = {Teskey, W. F. and Adler, D. H. and Teskey, W. J.},
    title = {{D}etermining free flight performance by surveying engineering techniques},
    journal = {{J} {S}urv {E}ng},
    year = {2006},
    volume = {132},
    number = {2},
    page = {93--96}
    }
  • R. C. Wilson, S. R. Das, and L. H. Finkel, “Motion as Shape: A Novel Method for Recognition and Prediction of Biological Motion,” in British Machine Vision Conference, 2006.
    [Bibtex]
    @INPROCEEDINGS{Wilson2006,
    author = {Wilson, R. C. and Das, S. R. and Finkel, L. H.},
    title = {{M}otion as {S}hape: {A} {N}ovel {M}ethod for {R}ecognition and {P}rediction
    of {B}iological {M}otion},
    booktitle = {{B}ritish {M}achine {V}ision {C}onference},
    year = {2006},
    abstract = {We introduce a method for the recognition and prediction of motion,
    based on the idea that different motions trace out different shapes
    in some state space. In the recognition step we use a multidimensional
    generalization of the shape context [12] to find the closest prototype
    motion to the observed data. When tested against motion capture data,
    our model yields excellent (99\%) recognition of gait and good (83\%)
    recognition of identity. In addition to recognition, this process
    also allows us to find an aligning transform TDP that maps the observed
    data D onto the prototype P. Given this transform, and its inverse
    TPD, we use a Bayesian approach to make optimal predictions about
    the data in the prototype space and then map these predictions back
    into data space. This approach gives accurate predictions over several
    gait cycles despite the fact that there is often a significant difference
    between the observed data and the prototype manifold.},
    owner = {srdas},
    publicationstatus = {Published},
    timestamp = {2014.02.19},
    uuid = {072AB252-42C2-4FBA-A94A-49BD16166735}
    }
  • B. Yu, P. A. Cook, H. Zhang, and D. Alexander, “Motion Correction in Diffusion Magnetic Resonance Imaging,” in Proceedings 13th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Seattle, 2006, p. 1068.
    [Bibtex]
    @INPROCEEDINGS{Bai2006ISMRM,
    author = {Yu, Bai and Cook, Philip A. and Zhang, Hui and Alexander, Daniel
    C.},
    title = {{M}otion {C}orrection in {D}iffusion {M}agnetic {R}esonance {I}maging},
    booktitle = {{P}roceedings 13th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {S}eattle},
    year = {2006},
    pages = {1068},
    abstract = {This abstract reveals an artifact in diffusion images introduced by
    standard motion and distortion correction methods for high angular-resolution
    acquisition and introduces a new correction scheme that avoids the
    artifact. The artifact is the misalignment of the tissues boundaries
    between T2 and FA maps. As our new methods choose different reference
    images for different diffusion gradients, they avoid the mismatching
    caused by the intensity differences between component images.},
    keywords = {Seattle1068}
    }

2005

  • P. A. Cook, H. Zhang, B. B. Avants, P. Yushkevich, D. C. Alexander, J. C. Gee, O. Ciccarelli, and A. J. Thompson, “An automated approach to connectivity-based partitioning of brain structures.,” Med Image Comput Comput Assist Interv, vol. 8, iss. Pt 1, pp. 164-171, 2005.
    [Bibtex]
    @ARTICLE{Cook2005MICCAI,
    author = {Cook, P. A. and Zhang, H. and Avants, B. B. and Yushkevich, P. and
    Alexander, D. C. and Gee, J. C. and Ciccarelli, O. and Thompson,
    A. J.},
    title = {{A}n automated approach to connectivity-based partitioning of brain
    structures.},
    journal = {{M}ed {I}mage {C}omput {C}omput {A}ssist {I}nterv},
    year = {2005},
    volume = {8},
    pages = {164--171},
    number = {Pt 1},
    abstract = {We present an automated approach to the problem of connectivity-based
    partitioning of brain structures using diffusion imaging. White-matter
    fibres connect different areas of the brain, allowing them to interact
    with each other. Diffusion-tensor MRI measures the orientation of
    white-matter fibres in vivo, allowing us to perform connectivity-based
    partitioning non-invasively. Our new approach leverages atlas-based
    segmentation to automate anatomical labeling of the cortex. White-matter
    connectivities are inferred using a probabilistic tractography algorithm
    that models crossing pathways explicitly. The method is demonstrated
    with the partitioning of the corpus callosum of eight healthy subjects.},
    institution = {{C}entre for {M}edical {I}mage {C}omputing, {D}epartment of {C}omputer
    {S}cience, {U}niversity {C}ollege {L}ondon, {UK}.},
    keywords = {Algorithms; Artificial Intelligence; Corpus Callosum, cytology; Diffusion
    Magnetic Resonance Imaging, methods; Humans; Image Enhancement, methods;
    Image Interpretation, Computer-Assisted, methods; Imaging, Three-Dimensional,
    methods; Nerve Fibers, Myelinated, ultrastructure; Pattern Recognition,
    Automated, methods; Reproducibility of Results; Sensitivity and Specificity},
    language = {eng},
    medline-pst = {ppublish},
    owner = {pcook},
    pmid = {16685842},
    timestamp = {2013.02.19}
    }
  • M. T. Lazarewicz, S. R. Das, and L. H. Finkel, “Recognition of temporal event sequences by a network of cortical neurons,” Neurocomputing, vol. 65-66, pp. 143-151, 2005.
    [Bibtex]
    @ARTICLE{Lazarewicz2005N,
    author = {Lazarewicz, M. T. and Das, S. R. and Finkel, L. H.},
    title = {{R}ecognition of temporal event sequences by a network of cortical
    neurons},
    journal = {{N}eurocomputing},
    year = {2005},
    volume = {65-66},
    pages = {143-151},
    abstract = {Recognition of ordered sequences of temporal events is central to
    many perceptual recognition tasks, from speech detection to analysis
    of biological motion. We describe a simple cortical network capable
    of recognizing event sequences through a process of encoding followed
    by detection. The network is composed of regular spiking and fast
    spiking neurons, with minimal connectivity. Ordered sequences of
    inputs occurring over tens-to-hundreds of milliseconds, are time
    compressed by the network into tightly clustered spike outputs occurring
    over a few milliseconds. We investigate the ability of the network
    to accurately encode the input pattern, in the presence or absence
    of noise. We show that information about relative input timings are
    preserved in the output interspike intervals.},
    owner = {srdas},
    publicationstatus = {Published},
    timestamp = {2014.02.19},
    uuid = {2420312F-C819-4952-A28E-55BCE902594E}
    }
  • M. Oleson, D. Adler, and P. Goldsmith, “A comparison of forefoot stiffness in running and running shoe bending stiffness,” J Biomech, vol. 38, iss. 9, 2005.
    [Bibtex]
    @ARTICLE{Oleson2005jbiomech,
    author = {Oleson, M. and Adler, D. and Goldsmith, P.},
    title = {{A} comparison of forefoot stiffness in running and running shoe
    bending stiffness},
    journal = {{J} {B}iomech},
    year = {2005},
    volume = {38},
    number = {9},
    page = {1886--1894}
    }
  • [DOI] E. D. Schwartz, J. Duda, J. S. Shumsky, E. T. Cooper, and J. Gee, “Spinal cord diffusion tensor imaging and fiber tracking can identify white matter tract disruption and glial scar orientation following lateral funiculotomy.,” J Neurotrauma, vol. 22, iss. 12, pp. 1388-1398, 2005.
    [Bibtex]
    @ARTICLE{Schwartz2005,
    author = {Schwartz, Eric D. and Duda, Jeffrey and Shumsky, Jed S. and Cooper,
    Emily T. and Gee, James},
    title = {{S}pinal cord diffusion tensor imaging and fiber tracking can identify
    white matter tract disruption and glial scar orientation following
    lateral funiculotomy.},
    journal = {{J} {N}eurotrauma},
    year = {2005},
    volume = {22},
    pages = {1388--1398},
    number = {12},
    month = {Dec},
    abstract = {Diffusion tensor magnetic resonance imaging (DTI) provides data concerning
    water diffusion in the spinal cord, from which white matter tracts
    may be inferred, and connectivity between spinal cord segments may
    be determined. We evaluated this potential application by imaging
    spinal cords from normal adult rats and rats that received cervical
    lateral funiculotomies, disrupting the rubrospinal tract (RST). Vitrogen
    and fibroblasts were transplanted into the surgical lesion at time
    of injury in order to fill the cavity. At 10 weeks, animals were
    sacrificed; the spinal cords were dissected out and then imaged in
    a 9.4-Tesla magnet. DTI tractography demonstrated the disruption
    of the rubrospinal tract axons while indicating which axon tracts
    were preserved. Additionally, DTI imaging could identify the orientation
    of glial processes in the gray matter adjacent to the site of injury.
    In the injured animals, reactive astrocytes in adjacent gray matter
    appeared to orient themselves perpendicular to white matter tracts.
    In summary, DTI identified not only white matter disruption following
    injury, but could distinguish the orientation of the accompanying
    glial scar.},
    doi = {10.1089/neu.2005.22.1388},
    institution = {{D}epartment of {R}adiology, {U}niversity of {P}ennsylvania {S}chool
    of {M}edicine, 1 {S}ilverstein, 3400 {S}pruce {S}treet, {P}hiladelphia,
    {PA} 19104, {USA}. {E}ric.{S}chwartz@uphs.upenn.edu},
    keywords = {Animals; Anisotropy; Axotomy; Diffusion Magnetic Resonance Imaging;
    Female; Neuroglia, pathology; Rats; Rats, Sprague-Dawley; Spinal
    Cord Injuries, pathology; Spinocerebellar Tracts, pathology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pmid = {16379577},
    timestamp = {2013.05.31},
    url = {http://dx.doi.org/10.1089/neu.2005.22.1388}
    }

2004

  • [DOI] P. A. Cook, D. C. Alexander, and G. Parker, “Modelling noise-induced fibre-orientation error in diffusion-tensor MRI,” in Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, 2004, p. 332-335 Vol. 1.
    [Bibtex]
    @INPROCEEDINGS{Cook2004ISBI,
    author = {Cook, P.A. and Alexander, D.C. and Parker, G.},
    title = {{M}odelling noise-induced fibre-orientation error in diffusion-tensor
    {MRI}},
    booktitle = {{B}iomedical {I}maging: {N}ano to {M}acro, 2004. {IEEE} {I}nternational
    {S}ymposium on},
    year = {2004},
    pages = {332-335 Vol. 1},
    abstract = {Diffusion-tensor MRI can be used to measure fibre orientation within
    the brain. Several studies have proposed methods to reconstruct known
    white matter fibre tracts in the brain. These methods are known as
    tractography. However, the measured fibre orientations are subject
    to error, which leads tractography methods to fail or define false
    connections. Probabilistic tractography methods use a model of the
    probability density function (PDF) of the local fibre orientation
    in each voxel, to calculate the likelihood of any potential fibre
    pathway through a DT data set. We propose the Watson distribution
    as a new fibre orientation PDF to replace ad hoc models used previously.
    We compare the probabilistic index of connectivity (PICo) tractography
    method using three candidate PDFs and show that the Watson PDF compares
    favourably to the ad hoc models.},
    doi = {10.1109/ISBI.2004.1398542},
    keywords = {biodiffusion;biomedical MRI;brain;image reconstruction;medical image
    processing;probability;Watson distribution;brain;diffusion-tensor
    MRI;noise-induced fibre-orientation error;probabilistic tractography;probability
    density function;white matter fibre tract reconstruction;Anisotropic
    magnetoresistance;Biomedical engineering;Biomedical imaging;Biomedical
    measurements;Brain;Computer errors;Diffusion tensor imaging;Eigenvalues
    and eigenfunctions;Magnetic resonance imaging;Tensile stress}
    }
  • [DOI] S. Das, M. Lazarewicz, and L. H. Finkel, “Principal component analysis of temporal and spatial information for human gait recognition.,” Conf Proc IEEE Eng Med Biol Soc, vol. 6, pp. 4568-71, 2004.
    [Bibtex]
    @ARTICLE{Das2004CPIEMBS,
    author = {Das, Sandhitsu and Lazarewicz, Maciej and Finkel, Leif H.},
    title = {{P}rincipal component analysis of temporal and spatial information
    for human gait recognition.},
    journal = {{C}onf {P}roc {IEEE} {E}ng {M}ed {B}iol {S}oc},
    year = {2004},
    volume = {6},
    pages = {4568-71},
    abstract = {Principal component analysis was applied to human gait patterns to
    investigate the role and relative importance of temporal versus spatial
    features. Datasets consisted of various limb and body angles sampled
    over increasingly long time intervals. We find that spatial and temporal
    cues may be useful for different aspects of recognition. Temporal
    cues contain information that can distinguish the phase of the gait
    cycle; spatial cues are useful for distinguishing running from walking.
    PCA and related techniques may be useful for identifying features
    used by the visual system for recognizing biological motion.},
    address = {United States},
    doi = {10.1109/IEMBS.2004.1404267},
    issn = {1557-170X},
    organization = {Department of Bioengineering, University of Pennsylvania, Philadelphia,
    PA 19104, USA.},
    owner = {srdas},
    primary_contributor_role = {Author},
    publicationstatus = {Published},
    pubmedid = {17271323},
    timestamp = {2014.02.19},
    us_nlm_id = {101243413},
    uuid = {0889AA68-0AE1-42F5-B91D-89B132CD45C9},
    web_data_source = {PubMed}
    }
  • S. R. Das, M. T. Lazarewicz, and L. H. Finkel, “Principal Component Analysis of Temporal and Spatial Information for Human Gait Recognition,” in Proceedings of the 26th Annual International Conference of IEEE Engineering in Medicine and Biology Society(EMBS), San Francisco, CA, 2004.
    [Bibtex]
    @INPROCEEDINGS{Das2004,
    author = {Das, S. R. and Lazarewicz, M. T. and Finkel, L. H.},
    title = {{P}rincipal {C}omponent {A}nalysis of {T}emporal and {S}patial {I}nformation
    for {H}uman {G}ait {R}ecognition},
    booktitle = {{P}roceedings of the 26th {A}nnual {I}nternational {C}onference of
    {IEEE} {E}ngineering in {M}edicine and {B}iology {S}ociety({EMBS})},
    year = {2004},
    address = {San Francisco, CA},
    owner = {srdas},
    publicationstatus = {Published},
    timestamp = {2014.02.19},
    uuid = {D0888962-7843-48DE-B0E1-4F4FE0DEC4A9}
    }
  • S. R. Das, M. T. Lazarewicz, and L. H. Finkel, Insights into Biological Motion Recognition from Principal Component Analysis of Human GaitPhiladelphia, PA: , 2004.
    [Bibtex]
    @MISC{Das2004PoB2,
    author = {Das, S. R. and Lazarewicz, M. T. and Finkel, L. H.},
    title = {{I}nsights into {B}iological {M}otion {R}ecognition from {P}rincipal
    {C}omponent {A}nalysis of {H}uman {G}ait},
    year = {2004},
    address = {Philadelphia, PA},
    journal = {{P}roceedings of {BMES} 2004},
    othertype = {Proceedings of BMES 2004},
    owner = {srdas},
    publicationstatus = {Published},
    timestamp = {2014.02.19},
    uuid = {9BAE8CC6-C776-4F41-A68F-AAE3CE7AE065}
    }
  • W. F. Teskey, R. J. Fox, and D. H. Adler, “Hidden Point Bar method for precise heighting,” J Surv Eng, vol. 130, iss. 4, 2004.
    [Bibtex]
    @ARTICLE{Teskey2004jsengg,
    author = {Teskey, W. F. and Fox, R. J. and Adler, D. H.},
    title = {{H}idden {P}oint {B}ar method for precise heighting},
    journal = {{J} {S}urv {E}ng},
    year = {2004},
    volume = {130},
    number = {4},
    page = {179--182}
    }
  • T. S. Yoo, Insight into images: principles and practice for segmentation, registration, and image analysis, AK Peters Wesllesley\^{} eMassachusetts Massachusetts, 2004, vol. 203.
    [Bibtex]
    @BOOK{Yoo2004,
    title = {{I}nsight into images: principles and practice for segmentation,
    registration, and image analysis},
    publisher = {AK Peters Wesllesley\^{} eMassachusetts Massachusetts},
    year = {2004},
    author = {Yoo, Terry S},
    volume = {203},
    owner = {jtduda},
    timestamp = {2013.05.31}
    }

2003

  • J. T. Duda, M. Rivera, D. C. Alexander, and J. C. Gee, “A method for non-rigid registration of diffusion tensor magnetic resonance images,” in Medical Imaging 2003, 2003, pp. 1186-1196.
    [Bibtex]
    @INPROCEEDINGS{Duda2003,
    author = {Duda, Jeffrey T and Rivera, Mariano and Alexander, Daniel C and Gee,
    James C},
    title = {{A} method for non-rigid registration of diffusion tensor magnetic
    resonance images},
    booktitle = {{M}edical {I}maging 2003},
    year = {2003},
    pages = {1186--1196},
    organization = {International Society for Optics and Photonics},
    owner = {jtduda},
    timestamp = {2013.05.31},
    url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=758229}
    }

2002

  • J. Duda, H. K. Song, R. Wolf, A. Wright, J. C. Gee, and F. W. Wehrli, “Method for quantitative assessment of atherosclerotic lesion burden on the basis of high-resolution black-blood MRI,” in Medical Imaging 2002, 2002, pp. 1798-1806.
    [Bibtex]
    @INPROCEEDINGS{Duda2002,
    author = {Duda, Jeffrey and Song, Hee K and Wolf, Ronald and Wright, Alex and
    Gee, James C and Wehrli, Felix W},
    title = {{M}ethod for quantitative assessment of atherosclerotic lesion burden
    on the basis of high-resolution black-blood {MRI}},
    booktitle = {{M}edical {I}maging 2002},
    year = {2002},
    pages = {1798--1806},
    organization = {International Society for Optics and Photonics},
    owner = {jtduda},
    timestamp = {2013.05.31},
    url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=880226}
    }
  • J. C. Gee, D. C. Alexander, M. Rivera, and J. T. Duda, “Non-rigid registration of diffusion tensor MR images,” in Proceedings IEEE International Symposim on Biomedical Imaging, 2002.
    [Bibtex]
    @INPROCEEDINGS{Gee2002IEEE,
    author = {Gee, James C. and Alexander, Daniel C. and Rivera, Mariano and Duda,
    Jeffrey T.},
    title = {{N}on-rigid registration of diffusion tensor {MR} images},
    booktitle = {{P}roceedings {IEEE} {I}nternational {S}ymposim on {B}iomedical {I}maging},
    year = {2002},
    location = {Piscataway}
    }
  • R. Wolf, J. T. Duda, H. K. Song, A. Wright, P. K. Saha, E. Mohler, and F. W. Wehrli, “Semi-automatic analysis of atherosclerotic lesion burden using an ellipse-fitting and histogram based thresholding method,” in Proceedings 10th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Honolulu, 2002, p. 1569.
    [Bibtex]
    @INPROCEEDINGS{Wolf2002ISMRM,
    author = {Wolf, Ronald and Duda, Jeffrey T. and Song, Hee K. and Wright, Alexander
    C. and Saha, P.K and Mohler, E. and Wehrli, Felix W.},
    title = {{S}emi-automatic analysis of atherosclerotic lesion burden using
    an ellipse-fitting and histogram based thresholding method},
    booktitle = {{P}roceedings 10th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {H}onolulu},
    year = {2002},
    pages = {1569},
    keywords = {Honolulu1569},
    url = {http://cds.ismrm.org/ismrm-2002/PDF6/1569.PDF}
    }

2001

  • B. Diehl, I. Najm, P. Ruggieri, J. Tkach, A. Mohamed, H. Morris, E. Wyllie, E. Fisher, J. Duda, M. Lieber, W. Bingaman, and H. O. Lüders, “Postictal diffusion-weighted imaging for the localization of focal epileptic areas in temporal lobe epilepsy.,” Epilepsia, vol. 42, iss. 1, pp. 21-28, 2001.
    [Bibtex]
    @ARTICLE{Diehl2001,
    author = {Diehl, B. and Najm, I. and Ruggieri, P. and Tkach, J. and Mohamed,
    A. and Morris, H. and Wyllie, E. and Fisher, E. and Duda, J. and
    Lieber, M. and Bingaman, W. and Lüders, H. O.},
    title = {{P}ostictal diffusion-weighted imaging for the localization of focal
    epileptic areas in temporal lobe epilepsy.},
    journal = {{E}pilepsia},
    year = {2001},
    volume = {42},
    pages = {21--28},
    number = {1},
    month = {Jan},
    abstract = {Diffusion-weighted MR imaging (DWI) is a novel technique to delineate
    focal areas of cytotoxic edema of various etiologies. We hypothesized
    that DWI may also detect the epileptogenic region and adjacent areas
    during the ictal and early postictal periods in patients with temporal
    lobe epilepsy (TLE).We studied patients with intractable TLE (n =
    9), due to hippocampal sclerosis (HS, n = 7), left mesial temporal
    lobe tumor (n = 1), and of unknown etiology (n = 1). Informed consent
    was obtained before inclusion in the study. All patients with single
    short seizures were scanned immediately after EEG-documented seizures
    (between 45 and 150 min); one of two patients in status was scanned
    14 h after cessation of seizures. DWI results were analyzed visually
    and by calculating apparent diffusion coefficient (ADC) maps.We found
    significant decreases in ADC postictally in one of six patients with
    TLE due to HS and single short seizures. One patient with an incompletely
    resected temporal lobe tumor also exhibited ADC abnormalities. One
    patient in focal status epilepticus revealed a decrease in ADC, and
    one patient with a continuous aura had no DWI abnormality.Postictal
    DWI technique may occasionally help delineate epileptic areas in
    some patients with TLE. Yield is low in patients with HS and single
    short seizures: it may be higher in patients with tumor or status
    epilepticus.},
    institution = {{D}epartment of {N}eurology, {T}he {C}leveland {C}linic {F}oundation,
    9500 {E}uclid {A}ve., {C}leveland, {O}hio 44195, {U}.{S}.{A}. diehlb@ccf.org},
    keywords = {Adolescent; Adult; Body Water, metabolism; Brain, metabolism; Diffusion;
    Electroencephalography, statistics /&/ numerical data; Epilepsy,
    Temporal Lobe, diagnosis/metabolism/physiopathology; Female; Hippocampus,
    metabolism/pathology; Humans; Magnetic Resonance Imaging, methods;
    Male; Middle Aged; Sclerosis, metabolism; Temporal Lobe, metabolism/physiopathology},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pii = {epi19500},
    pmid = {11207781},
    timestamp = {2013.05.31}
    }

2000

  • P. J. Basser, S. Pajevic, C. Peirpaoli, A. Aldroubi, and J. T. Duda, “Fiber-tractography in human brain using diffusion tensor MRI DT-MRI,,” in Proceedings 8th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Denver, 2000, p. 784.
    [Bibtex]
    @INPROCEEDINGS{Basser2000ISMRM,
    author = {Basser, Peter J. and Pajevic, Sini and Peirpaoli, Carlo and Aldroubi,
    Akram and Duda, Jeffrey T.},
    title = {{F}iber-tractography in human brain using diffusion tensor {MRI}
    {DT}-{MRI},},
    booktitle = {{P}roceedings 8th {S}cientific {M}eeting, {I}nternational {S}ociety
    for {M}agnetic {R}esonance in {M}edicine, {D}enver},
    year = {2000},
    pages = {784},
    keywords = {Denver784},
    url = {http://cds.ismrm.org/ismrm-2000/PDF3/0784.pdf}
    }
  • P. J. Basser, S. Pajevic, C. Pierpaoli, J. Duda, and A. Aldroubi, “In vivo fiber tractography using DT-MRI data.,” Magn Reson Med, vol. 44, iss. 4, pp. 625-632, 2000.
    [Bibtex]
    @ARTICLE{Basser2000,
    author = {Basser, P. J. and Pajevic, S. and Pierpaoli, C. and Duda, J. and
    Aldroubi, A.},
    title = {{I}n vivo fiber tractography using {DT}-{MRI} data.},
    journal = {{M}agn {R}eson {M}ed},
    year = {2000},
    volume = {44},
    pages = {625--632},
    number = {4},
    month = {Oct},
    abstract = {Fiber tract trajectories in coherently organized brain white matter
    pathways were computed from in vivo diffusion tensor magnetic resonance
    imaging (DT-MRI) data. First, a continuous diffusion tensor field
    is constructed from this discrete, noisy, measured DT-MRI data. Then
    a Frenet equation, describing the evolution of a fiber tract, was
    solved. This approach was validated using synthesized, noisy DT-MRI
    data. Corpus callosum and pyramidal tract trajectories were constructed
    and found to be consistent with known anatomy. The method's reliability,
    however, degrades where the distribution of fiber tract directions
    is nonuniform. Moreover, background noise in diffusion-weighted MRIs
    can cause a computed trajectory to hop from tract to tract. Still,
    this method can provide quantitative information with which to visualize
    and study connectivity and continuity of neural pathways in the central
    and peripheral nervous systems in vivo, and holds promise for elucidating
    architectural features in other fibrous tissues and ordered media.},
    institution = {{S}ection on {T}issue {B}iophysics and {B}iomimetics, {NICHD}, {B}ethesda,
    {M}aryland 20892-5772, {USA}. pjbasser@helix.nih.gov},
    keywords = {Artifacts; Brain, anatomy /&/ histology; Humans; Image Processing,
    Computer-Assisted; Magnetic Resonance Imaging, methods; Nerve Fibers},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pii = {3.0.CO;2-O},
    pmid = {11025519},
    timestamp = {2013.05.31}
    }
  • R. A. Rudick, E. Fisher, J. C. Lee, J. T. Duda, and J. Simon, “Brain atrophy in relapsing multiple sclerosis: relationship to relapses, EDSS, and treatment with interferon beta-1a.,” Mult Scler, vol. 6, iss. 6, pp. 365-372, 2000.
    [Bibtex]
    @ARTICLE{Rudick2000,
    author = {Rudick, R. A. and Fisher, E. and Lee, J. C. and Duda, J. T. and Simon,
    J.},
    title = {{B}rain atrophy in relapsing multiple sclerosis: relationship to
    relapses, {EDSS}, and treatment with interferon beta-1a.},
    journal = {{M}ult {S}cler},
    year = {2000},
    volume = {6},
    pages = {365--372},
    number = {6},
    month = {Dec},
    abstract = {Brain atrophy is a relevant surrogate marker of the disease process
    in multiple sclerosis (MS) because it represents the net effect of
    various pathological processes leading to brain tissue loss. There
    are various approaches to quantifying central nervous system atrophy
    in MS. We have focused on a normalized measure of whole brain atrophy,
    the brain parenchymal fraction (BPF). BPF is defined as the brain
    parenchymal volume, divided by the volume within the surface of the
    brain. We applied this method to an MRI data set generated during
    a phase III clinical trial of interferon beta-1a (AVONEX). The purpose
    of the current study is to further explore clinical and MRI correlates
    of the BPF, particularly as they relate to relapse rate and Kurtzke's
    Expanded Disability Status Score (EDSS); and to further explore the
    therapeutic effects observed in interferon beta-1a recipients. Of
    all demographic and disease measures in the clinical trial data base,
    T2 lesion volume most closely correlated with BPF in cross sectional
    studies, and was the baseline factor most closely correlated with
    progressive brain atrophy in the subsequent 2 years. We also observed
    that change in T2 lesion volume was the disease measure most closely
    correlated with change in BPF during 2 years of observation. Of interest,
    relapse number and EDSS change during 2 years were only weakly correlated
    with BPF change during the same period. Disability progression, defined
    as sustained worsening of at least 1.0 EDSS points from baseline,
    persisting at least 6 months, was associated with significantly greater
    brain atrophy progression. We observed a therapeutic effect of interferon
    beta-1a in the second year of the clinical trial, and this beneficial
    effect was not accounted for by change in gadolinium enhanced lesion
    volume, or by corticosteroid medication within 40 days of the final
    MRI scan. The BPF is an informative surrogate marker for destructive
    pathological processes in relaping MS patients, and is useful in
    demonstrating treatment effects in controlled clinical trials. The
    significance of progressive brain atrophy during relapsing MS will
    be assessed by measuring clinical and MRI changes in prospective
    follow up studies.},
    institution = {{D}epartment of {N}eurology, {M}ellon {C}enter, {T}he {C}leveland
    {C}linic {F}oundation, {O}hio 44195, {USA}.},
    keywords = {Adjuvants, Immunologic, therapeutic use; Adult; Atrophy; Brain, drug
    effects/pathology/physiopathology; Clinical Trials, Phase III as
    Topic; Cohort Studies; Disability Evaluation; Follow-Up Studies;
    Humans; Interferon-beta, therapeutic use; Magnetic Resonance Imaging;
    Multicenter Studies as Topic; Multiple Sclerosis, Relapsing-Remitting,
    drug therapy/pathology/physiopathology; Prospective Studies; Randomized
    Controlled Trials as Topic; Treatment Outcome},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pmid = {11212130},
    timestamp = {2013.05.31}
    }

1999

  • B. Diehl, I. Najm, P. Ruggieri, N. Foldvary, A. Mohamed, J. Tkach, H. Morris, G. Barnett, E. Fisher, J. Duda, and H. O. Lüders, “Periictal diffusion-weighted imaging in a case of lesional epilepsy.,” Epilepsia, vol. 40, iss. 11, pp. 1667-1671, 1999.
    [Bibtex]
    @ARTICLE{Diehl1999,
    author = {Diehl, B. and Najm, I. and Ruggieri, P. and Foldvary, N. and Mohamed,
    A. and Tkach, J. and Morris, H. and Barnett, G. and Fisher, E. and
    Duda, J. and Lüders, H. O.},
    title = {{P}eriictal diffusion-weighted imaging in a case of lesional epilepsy.},
    journal = {{E}pilepsia},
    year = {1999},
    volume = {40},
    pages = {1667--1671},
    number = {11},
    month = {Nov},
    abstract = {Diffusion-weighted MR imaging (DWI) has been used for the early diagnosis
    of acute ischemic lesions in humans and in animal models of focal
    status epilepticus. We hypothesized that DWI may be a sensitive,
    noninvasive tool for the localization of the epileptogenic area during
    the periictal period.A periictal DWI study was performed on a 35-year-old
    patient during focal status epilepticus with repetitive prolonged
    focal motor seizures originating from a lesion in the right frontal
    lobe. DWI results were analyzed visually and by calculating apparent
    diffusion coefficient (ADC) maps.On DWI, a single area of signal
    increase (decrease in ADC) was found in the region of focal electrocorticographic
    seizures that was mapped intraoperatively.Ictal/postictal DWI may
    be a useful technique for seizure localization in patients with lesional
    epilepsy.},
    institution = {{D}epartment of {N}eurology, {T}he {C}leveland {C}linic {F}oundation,
    {O}hio, {USA}. diehlb@ccf.org},
    keywords = {Adult; Brain Neoplasms, diagnosis/pathology/surgery; Echo-Planar Imaging,
    methods/statistics /&/ numerical data; Electroencephalography, statistics
    /&/ numerical data; Epilepsies, Partial, diagnosis/pathology/surgery;
    Female; Frontal Lobe, pathology/surgery; Glioma, diagnosis/pathology/surgery;
    Humans},
    language = {eng},
    medline-pst = {ppublish},
    owner = {jtduda},
    pmid = {10565599},
    timestamp = {2013.05.31}
    }