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Abstract #3747

THOMAS: Thalamus Optimized Multi-Atlas Segmentation

Jason Su 1,2 , Thomas Tourdias 3 , Manojkumar Saranathan 2 , and Brian K. Rutt 2

1 Electrical Engineering, Stanford University, Stanford, California, United States, 2 Radiology, Stanford University, Stanford, California, United States, 3 Neuroradiology, Bordeaux University Hospital, Bordeaux, France

A method for automatic segmentation of thalamic nuclei was developed and optimized using 7T white-matter-nulled MP-RAGE images, which provide excellent contrast and detail for segmentation and for ANTS nonlinear registration. The PICSL multi-atlas label fusion algorithm by Wang and Yushkevich was optimized for 12 thalamic nuclei and validated in 9 subjects using an atlas of prior manual delineations from 20 subjects, including multiple sclerosis patients and healthy controls. Performance in accuracy, resolution, and acquisition time surpasses other published methods that require DTI. The Dice coefficients for whole thalamus (0.92), pulvinar nucleus (0.86), and mediodorsal nucleus (0.87) were notably high.

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