Abstract #2707

A novel DWI-based thalamus segmentation method using Constrained Spherical Deconvolution

Charles Iglehart¹, Adam Bernstein², Martin Monti^3,4, Joshua A. Cain³, and Manojkumar Saranathan^1,5

¹Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States, ²Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States, ³Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States, ⁴Department of Neurosurgery Brain Research Center, University of California, Los Angeles, Los Angeles, CA, United States, ⁵Department of Medical Imaging, University of Arizona, Tucson, AZ, United States

Existing methods to segment the thalamus via diffusion weighted MRI are inhibited by several factors. The largely gray matter composition of the thalamus makes the local diffusion activity indistinct and some of the more successful DWI-based methods require time consuming and computationally expensive cortical parcellation for thalamus masking. This study addresses these limitations by using multi-tissue constrained spherical deconvolution to isolate desired diffusion activity and a novel template based technique for thalamus masking. Segmentation outputs are evaluated and we conclude with a discussion of the method’s advantages over existing techniques.

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