Study And Implementation On Fiber Tracking Algorithm Of White Matter Based On Diffusion Tensor Imaging Data

The brain nervous system is one of the most complex parts in the human body. It plays an important role of information transmission. So it is significant to visualize the nerve fibers of white matter quickly, accurately and real-time. Since the structure of the nerve fibers is anfractuous, however, it is impossible to accurately portray the nerve fibers in the human brain even using the medical anatomic methods.With the development of magnetic resonance imaging technology, one unique method named MR diffusion tensor imaging (DTI) is introduced to reconstruct neural fibers in the brain white matter. It can be used in neurological diagnosis, surgical navigation and the research on the brain development and some brain diseases. Gradually, this study shows great significance in the brain science field.So far, researchers have proposed many types of visualization techniques of the nerve fibers. And the technique based on the diffusion of the brain white matter is the most popular one. This graduation project implemented two kinds of fiber tracking algorithms, which based on the diffusion shape and Streamline Tracking (STT), respectively. The algorithm based on the diffusion shape combined the advantages of STT and Tensor Deflection (TEND), and used different tracking strategies according to diffusion anisotropy. The reconstruction result was closer to the real fiber than that of STT, especially in case of planar diffusion. Before the reconstruction algorithm, the trilinear interpolation difference to the key parameters (eigen vector, eigen values and so on) would improve the reconstruction significantly. In general, the algorithm based on the diffusion shape can track the brain nerve fibers more completely and accurately.