White Matter Tract Clustering and Correspondence in Populations


L. O'Donnell, C.-F. Westin
Eighth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'05)
Pages 140-147
October, 2005

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Abstract

We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every brain. Using spectral methods we embed each path as a vector in a high dimensional space. We create the embedding space so that it is common across all brains, consequently similar paths in all brains will map to points near each other in the space. By performing clustering in this space we are able to find matching fiber tract clusters in all brains. In addition, we automatically obtain correspondence of tractographic paths across brains: by selecting one or several paths of interest in one brain, the most similar paths in all brains are obtained as the nearest points in the high-dimensional space.

Anatomical correspondences: selected clusters, displayed in all 5 brains. The two leftmost images show the corpus callosum viewed superiorly and from the right. Of the 100 clusters found, 10 were manually chosen as belonging to the corpus callosum. The third images from the left show a single cluster containing the cingulum bundles, viewed superiorly. Finally, the rightmost images show the two clusters that contain the left and right uncinate fasciculi, viewed anteriorly and from the right.

Reference

O'Donnell L, Westin CF. White matter tract clustering and correspondence in populations. In Eighth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'05), Lecture Notes in Computer Science 3749. Palm Springs, CA, USA, 2005;140-147.

Bibtex entry

@InProceedings{odonnellMICCAI05,
  author         = {L. O'Donnell and C.-F. Westin},
                           
  title          = {White Matter Tract Clustering and Correspondence in        
                   Populations},
                                              
  booktitle      = {Eighth International Conference on Medical Image Computing 
                   and 
 Computer-Assisted Intervention (MICCAI'05)},
         
  pages          = {140--147},
                                                
  year           = {2005},
                                                    
  series         = {Lecture Notes in Computer Science 3749},
                  
  address        = {Palm Springs, CA, USA},
                                   
  month          = {October}
}

Grants

NIH R01-NS051826, NIH U24-RR021382, NIH U54-EB005149 (NAMIC)

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