Segmentation of thalamic nuclei from DTI using spectral clustering

Authors:
Ulas Ziyan;David Tuch;Carl-Fredrik Westin
Affiliations:
MIT Computer Science and Artificial Intelligence Lab, Cambridge, MA;Novartis Pharma AG, Basel, Switzerland;MIT Computer Science and Artificial Intelligence Lab, Cambridge, MA
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Year:
2006

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Abstract

Recent work shows that diffusion tensor imaging (DTI) can help resolving thalamic nuclei based on the characteristic fiber orientation of the corticothalamic/thalamocortical striations within each nucleus. In this paper we describe a novel segmentation method based on spectral clustering. We use Markovian relaxation to handle spatial information in a natural way, and we explicitly minimize the normalized cut criteria of the spectral clustering for a better optimization. Using this modified spectral clustering algorithm, we can resolve the organization of the thalamic nuclei into groups and subgroups solely based on the voxel affinity matrix, avoiding the need for explicitly defined cluster centers. The identification of nuclear subdivisions can facilitate localization of functional activation and pathology to individual nuclear subgroups.