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Abstract #4019

False Positive Detection Using Filtered Tractography

Yogesh Rathi1,2, James Malcolm, 23, Sylvain Bouix1, C-F Westin4, Martha E. Shenton1,5

1Psychiatry, Harvard Medical School, Boston, MA, United States; 2Georgia Institute of Technology, Atlanta, GA, United States; 3Brigham and Women's Hospital, United States; 4Radiology, Harvard Medical School, Boston, MA, United States; 5VA Clinical Neuroscience Division, Boston, MA, United States

Existing methods perform model estimation independently at each voxel and tractography is performed in the next step. We use a nonlinear Kalman filter for simultaneous model estimation and tractography. The method not only provides an estimate of the model parameters, but also a confidence in the estimation in terms of the covariance matrix. We utilize measures derived from this covariance matrix to detect false positives in the tracts generated.