High-dimensional white matter atlas generation and group analysis

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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. © Springer-Verlag Berlin Heidelberg 2006.

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APA

O’Donnell, L., & Westin, C. F. (2006). High-dimensional white matter atlas generation and group analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4191 LNCS-II, pp. 243–251). Springer Verlag. https://doi.org/10.1007/11866763_30

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