• DocumentCode
    3506944
  • Title

    Structural connectivity via the tensor-based morphometry

  • Author

    Kim, Seung-Goo ; Chung, Moo K. ; Hanson, Jamie L. ; Avants, Brian B. ; Gee, James C. ; Davidson, Richard J. ; Pollak, Seth D.

  • Author_Institution
    Dept. of Brain & Cognitive Sci., Seoul Nat. Univ., Seoul, South Korea
  • fYear
    2011
  • fDate
    March 30 2011-April 2 2011
  • Firstpage
    808
  • Lastpage
    811
  • Abstract
    The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the e-neighbor method that does not need any predetermined parcellation. The proposed pipeline is applied in detecting the topological alteration of the white matter connectivity in maltreated children.
  • Keywords
    biomedical MRI; brain; paediatrics; T1-weighted magnetic resonance imaging; brain network graph; diffusion tensor imaging; predetermined parcellation; structural connectivity; tensor-based morphometry; tissue volume difference; white matter connectivity; Biomedical imaging; Brain modeling; Correlation; Diffusion tensor imaging; Joining processes; Neuroscience; Jacobian determinant; brain network; maltreatment; structural connectivity; tensor-based morphometry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
  • Conference_Location
    Chicago, IL
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-4127-3
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2011.5872528
  • Filename
    5872528