Comparison of Parametric and Nonparametric Probabilistic White Matter Tractography Methods
Lazar M, Alexander A
University of Wisconsin
Probabilistic white matter tractography methods have been proposed to account for the uncertainty in the local fiber direction estimation due to image noise and artifacts. The goal of this study was to compare the performances of one parametric probabilistic tractography method, the random vector perturbation (RAVE) algorithm, against a non-parametric bootstrap tractography (BOOT-TRAC) method. The RAVE algorithm appears to generate fiber distributions similar to the BOOT-TRAC algorithm for trajectories situated in homogeneous white matter regions and might be a viable substitute for BOOT-TRAC in cases when multiple measurements of the diffusion-weighted images are not available or are difficult to obtain.