White Matter Fiber Tracts Based On Diffusion Tensor Imaging

The recently developed magnetic resonance imaging technique of diffusion tensor imaging (DTI) has a widespread application on investigating the cerebral white matter architecture. When referred to fiber tracking, as the typical application of DTI, one of the most intuitive ways to reconstruct fiber trajectory is streamline tracking, (STT). Regarding the problems from noise and discrete tensor field in traditional STT algorithm, we introduce the concept of adjacent and previous voxels as well as the break point during fiber tracking. To evaluate the validity of our improved algorithm, we firstly applied it on the simulated data and meanwhile obtained some available values in our approach. Then the traditional STT and improved algorithm were both applied to DTI data to reconstruct the fiber trajectory. The results showed our improved method did follow the actual fiber more precisely. Future improvements were also discussed in the end of the paper.

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