Joint segmentation of thalamic nuclei from a population of diffusion tensor MR images

Ulas Ziyan and Carl-Fredrik Westin. 2008. Joint segmentation of thalamic nuclei from a population of diffusion tensor MR images. Med Image Comput Comput Assist Interv, 11, Pt 1, Pp. 279-86.
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Abstract

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.
Last updated on 02/24/2023