Regularized stochastic white matter tractography using diffusion tensor MRI

Abstract

The development of Diffusion Tensor MRI has raised hopes in the neuro-science community for in vivo methods to track fiber paths in the white matter. A number of approaches have been presented, but there are still several essential problems that need to be solved. In this paper a novel fiber propagation model is proposed, based on stochastics and regularization, allowing paths originating in one point to branch and return a probability distribution of possible paths. The proposed method utilizes the principles of a statistical Monte Carlo method called Sequential Importance Sampling and Resampling (SISR).