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Abstract #1910

Logical Foundations and Fast Implementation of Probabilistic Tractography

Myron Zhang1, 2, Ken E. Sakaie1, Jones Stephen1

1Imaging Institute, The Cleveland Clinic, Cleveland, OH, United States; 2Physics, Cornell University, Ithaca, NY, United States

Maps of whole-brain anatomical connections generated by tractography prove valuable for identifying targets for resection in the treatment of phamacoresistant epilepsy. Unfortunately, current implementations have difficulty identifying a number of important connections while relying on intuitively appealing but ad-hoc logic. In this contribution, we present a logical formulation of probabilistic tractography that lends itself to fast implementation. The method identifies connections throughout the entire brain and may prove important for presurgical planning and other medical applications.