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High-Dimensional White Matter Atlas Generation and Group Analysis

  • Lauren O’Donnell
  • Carl-Fredrik Westin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

We present a two-step process including white matter atlas generation and automatic segmentation. Our atlas generation method is based on population fiber clustering. We produce an atlas which contains high-dimensional descriptors of fiber bundles as well as anatomical label information. We use the atlas to automatically segment tractography in the white matter of novel subjects and we present quantitative results (FA measurements) in segmented white matter regions from a small population. We demonstrate reproducibility of these measurements across scans. In addition, we introduce the idea of using clustering for automatic matching of anatomical structures across hemispheres.

Keywords

White Matter White Matter Tract Automatic Segmentation Uncinate Fasciculus Midsagittal Plane 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lauren O’Donnell
    • 1
    • 2
  • Carl-Fredrik Westin
    • 1
    • 3
  1. 1.Computer Science and Artificial Intelligence LaboratoryMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Harvard-MIT Division of Health Sciences and TechnologyCambridgeUSA
  3. 3.Laboratory for Mathematics in ImagingBrigham and Women’s Hospital, Harvard Medical SchoolBostonUSA

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