High-Dimensional White Matter Atlas Generation and Group Analysis

Lauren O'Donnell, C.-F. Westin
Ninth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'06)
Pages 243-251
October, 2006

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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.

Result of automatic segmentation of novel subjects (11-13). Selected regions are shown as follows: navy blue, corpus callosum; yellow, corticospinal fibers; purple, arcuate fasciculus/SLF region; orange, uncinate fasciculus; green, inferior longitudinal fasciculus; sky blue, middle cerebellar peduncle; light pink, superior cerebellar peduncle; hot pink, inferior occipitofrontal fasciculus.

Reference

O'Donnell L, Westin CF. High-dimensional white matter atlas generation and group analysis. In Ninth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'06), Lecture Notes in Computer Science 4191. Copenhagen, Denmark, 2006;243-251.

Bibtex entry

@InProceedings{odonnellMICCAI06,
  author         = "Lauren O'Donnell and Carl-Fredrik Westin",                 
  title          = "High-Dimensional White Matter Atlas Generation and Group   
                   Analysis",                                                  
  booktitle      = "Ninth International Conference on Medical Image Computing  
                   and Computer-Assisted Intervention (MICCAI'06)",            
  month          = "October",                                                  
  year           = "2006",                                                     
  pages          = "243--251",                                                 
  series         = "Lecture Notes in Computer Science 4191",                   
  address        = "Copenhagen, Denmark"}

Grants

NIH U54-EB005149 (NAMIC), NIH P41-RR13218 (NAC), NIH U24-RR021382, NIH R01-MH50747

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