Abstract #4328

THOMAS: Thalamus Optimized Multi-Atlas Segmentation at 3T

Jason Su¹, Thomas Tourdias², Manojkumar Saranathan³, Pejman Ghanouni⁴, and Brian Rutt⁴

¹Electrical Engineering, Stanford University, Stanford, CA, United States, ²Neuroradiology, Bordeaux University Hospital, Bordeaux, France, ³Radiology, University of Arizona, Tucson, AZ, United States, ⁴Radiology, Stanford University, Stanford, CA, United States

The efficacy of the Thalamus Optimized Multi-Atlas Segmentation (THOMAS) algorithm for segmentation of thalamic nuclei with white-matter-nulled MP-RAGE images is studied in 3T and 7T variants of the image contrast. 5 subjects are evaluated at both field strengths and ground truth manual delineations of nuclei are performed on the 7T images. We demonstrate that the algorithm performs as well on 3T images as on 7T within a dice coefficient of ±0.1 as evaluated against the ground truth. This indicates that THOMAS can now reach a much wider audience of interested groups.

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