Study and preliminary application of an improved fiber tracking algorithm in central nervous system

As a noninvasive fiber visualization imaging technique, DTI has been developed rapidly in recent years. It has been considered to have high potential value in the diagnosis and treatment of the nervous system diseases. And in the applications of DTI, the fiber tracking algorithm is critical to the visualization results. So far, researchers have proposed many 3D visualization methods. Among them, Fiber Assignment by Continuous Tracking (FACT) algorithm is the most commonly used one, especially in white matter fiber tracking. But it is powerless to deal with the fiber crossing problem. In this paper, based on FACT algorithm under traditional single-tensor model, two-tensor model is enrolled to try to solve this kind of problem. We proposed a better fiber tracking way by the combination of these two models. At last, we applied it to some nervous system diseases.