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Abstract #3960

A Full Bi-Tensor Neural Tractography Algorithm using the Unscented Kalman Filter

Stefan Lienhard1, James Malcolm2, Carl-Frederik Westin3, Yogesh Rathi2

1Information Technology & Electrical Engineering, ETH Zrich, Zrich, Switzerland; 2Harvard Medical School, Psychiatry Neuroimaging Laboratory, Boston, MA, United States; 3Harvard Medical School, Laboratory of Mathematics in Imaging, Boston, MA, United States

We introduce a tractography method by extending an existing framework which models the signal with Gaussian tensors. At each fiber point an unscented Kalman filter finds the most consistent direction as a mixture of previous estimates and of the local model. In the existing framework the diffusion tensors second and third eigenvalues are identical. We extend the tensor representation so that the diffusion tensor can be an arbitrary ellipsoid. Synthetic experiments show better angular resolution at fiber crossings. Tests on in vivo data show that our new model finds fibers in areas where the simpler model stops.