Gang Song

gang

Research Overview

Research focuses in computational algorithms of quantitative analysis of medical images of various modalities, both in vivo and ex vivo, for disease analysis, diagnosis and quantification. Modalities include computed tomography, magnetic resonance imaging and histology. Specially interested in building analysis pipeline of serial CT volumetric images for registration, segmentation and analysis of pulmonary kinematics. Research also includes reconstruction of serial histology 2D slices into 3D space and normalization with volumetric atlas.

Projects

  • Feature Selection for Characterization of ILD and COPD
    The performance of various image-based metrics computed from thoracic HRCT modality were compared with data from pulmonary function testing (PFT) in characterizing interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD). Results showed that some image metrics are not only as good discriminators as PFT for characterization of ILD and COPD, but also not redundant when PFT values are provided.

Education

  • May 2006 – Aug 2013 PhD in Computer and Information Science, University of Pennsylvania, Philadelphia, PA
  • June 2004 – May 2006 MS. in Computer and Information Science, University of Pennsylvania, Philadelphia, PA
  • Sep. 2001 – Jan. 2004 MS in Computer Science and Technology, Tsinghua University, Beijing, China
  • Sep. 1997 – June 2001 BE in Computer Science and Technology, Tsinghua University, Beijing, China

Publications

  • 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}
    }