Fast and accurate segmentation of deep gray matter regions in the brain is important for clinical applications such as surgical planning for the placement of deep brain stimulation implants. Mapping anatomy from stereotactic atlases to patient data is problematic because of individual differences in subject anatomy that are not accounted for by commonly used atlases. We present a segmentation method for individual subject diffusion tensor MR data that is based on local diffusion information to identify subregions of the thalamus. We show the correspondence of our segmentation results to anatomy by comparison with stereotactic atlas data. Importantly, we verify the consistency of our segmentation by evaluating the method on 63 healthy volunteers. Our method is fast, reliable, and independent of any segmentation before the classification of regions within the thalamus. It should, therefore, be useful in clinical applications.
Copyright © 2011 Wiley-Liss, Inc.