Generalized Diffusion Simulation-Based Tractography

Diffusion weighted imaging (DWI) techniques have been used to study human brain white matter fiber structures in vivo. Commonly used standard diffusion tensor magnetic resonance imaging (DTI) tractography derived from the second order diffusion tensor model has limitations in its ability to resolve complex fiber tracts. We propose a new fiber tracking method based on the generalized diffusion tensor (GDT) model. This new method better models the anisotropic diffusion process in human brain by using the generalized diffusion simulation-based fiber tractography (GDST). Due to the additional information provided by GDT, the GDST method simulates the underlying physical diffusion process of the human brain more accurately than does the standard DTI method. The effectiveness of the new fiber tracking algorithm was demonstrated via analyses on real and synthetic DWI datasets. In addition, the general analytic expression of high order b matrix is derived in the case of twice refocused spin-echo (TRSE) pulse sequence which is used in the DWI data acquisition. Based on our results, we discuss the benefits of GDT and the second order diffusion tensor on fiber tracking.