A Coupled Multi-shape Representation

J. Malcolm, Y. Rathi, M.E. Shenton, A. Tannenbaum
Pages 416-424
September, 2008

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Several recent studies explored the use of unsupervised segmentation methods for segmenting thalamic nuclei from diffusion tensor images. These methods provide a plausible segmentation on individual subjects; however, they do not address the problem of consistently identifying the same functional areas in a population. The lack of correspondence between the segmented nuclei make it more difficult to use the results from the unsupervised segmentation tools for morphometry. In this paper we present a novel segmentation algorithm to automatically segment the gray matter nuclei while ensuring consistency between subjects in a population. This new algorithm, referred to as Consistency Clustering, finds correspondence between the nuclei as the segmentation is achieved through a single model for the whole population, similar to the brain atlases experts use to identify thalamic nuclei.


Malcolm J, Rathi Y, Shenton M, Tannenbaum A. A coupled multi-shape representation. In miccai. 2008;416-424.


NIH NAC P41 RR13218, Marie Curie Grant through the Technion, Israel Institute of Technology, NIH U54 EB005149

Research areas

registration, shapeanalysis
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