Cocluster analysis of thalamo-cortical fibre tracts extracted from diffusion tensor MRI. (22nd December 2008)

• Record Type: Journal Article
• Authors: Lin, Cui; Lu, Shiyong; Liang, Xuwei; Hua, Jing; Muzik, Otto
• Is Part Of: International journal of data mining and bioinformatics. Volume 2:Number 4(2008)
• Page Start: 342
• Page End: 361
• Publication Date: 2008-12-22
• Subjects: coclustering -- cortex -- thalamus segmentation -- fibre tracking -- thalamo-cortical connectivity -- data mining -- bioinformatics -- cocluster analysis -- human brain -- thalamic nuclei -- cortical projections -- clustering -- genetic algorithms -- GAs -- fibre tracts -- cortical voxels -- thalamic voxels; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

As the central relay station of the human brain, the thalamus modulates sensory signals to and from the cerebral cortex. The reciprocal connectivity between the cerebral cortex and the thalamus is believed to play an essential role in consciousness and various neurological disorders. Thus, in-vivo analysis of thalamo-cortical connectivity is important for our understanding of normal and pathological brain processes. In this paper, we propose a new partitioning paradigm, called coclustering, in order to segment the thalamus into thalamic nuclei based on their cortical projections. In contrast to the traditional clustering paradigm, a coclustering procedure not only simultaneously partitions cortical voxels and thalamic voxels into groups, but also identifies the corresponding strong connectivities between the two classes of groups. We develop the first coclustering algorithm, Genetic Coclustering Algorithm (GCA), to solve the coclustering problem. We apply GCA to segment the thalamus into thalamic nuclei and visualise main thalamo-cortical fibre tracts.