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Philip Cook

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Research

My primary research interests are in pipelines for multi-modal MRI studies of the brain. I approach from two perspectives. As a software developer, I contribute to Camino, ANTs and ANTsR, and PipeDream. As an imaging scientist, I use these and other tools in studies of dementia, stress neurobiology and traumatic brain injury.

More about me

My Google Scholar pageGitHub and SourceForge.

A list of posts by me on this site.

Some other tools I use: ITK-SNAP (for pretty much everything), DTI-TK (DTI registration and Tract Specific Analysis, example), MRIcron (mostly for Dicom to NIfTI conversion).

Education

University College London

  • BSc astrophysics 2000
  • MSc computer science 2001
  • PhD computer science 2006

My thesis work focused on the development of parametric methods to estimate uncertainty in probabilistic tractography using multi-fiber reconstruction techniques, and methods to maintain even spherical coverage during diffusion acquisition. The implementation is available in the Camino toolkit.

Selected journal and conference publications

  • [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}
    }
  • [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}
    }
  • [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}
    }
  • [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] 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}
    }
  • [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}
    }
  • 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}
    }
  • 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}
    }
  • [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] 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] 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] 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}
    }
  • [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}
    }
  • 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}
    }
  • [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}
    }
  • [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}
    }
  • [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}
    }
  • [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}
    }
  • 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}
    }

Selected short conference papers and abstracts

  • 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}
    }
  • 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] 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}
    }
  • 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}
    }
  • 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. 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}
    }
  • [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}
    }