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Home arrow Computer Science arrow Computational Diffusion MRI: MICCAI Workshop, Athens, Greece, October 2016



We presented a parcellation result using dMRI data, demonstrating areal definitions that reflect some well known architectonically defined regions without the use of a training stage or any non-local spatial constraints. The population average feature set is most discriminative in primary areas that are consistently located across subjects, such as S-I and M-I, and heavily myelinated regions. However, we also observe clusters that may correspond to non-primary areas such as area 44 and 45. Our results demonstrate that the higher-order, diffusion-based, feature set may be distinguishing local differences in the texture and geometry of the myelinated meshwork of the neocortex not all of which are visible in myelin density maps. Incorporating this information is likely to improve the performance of non- supervised multimodal parcellation schemes for cortical areas.


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