Weighted geometric diffusion measures for neuronal fiber tractography algorithms

A fiber tracking algorithm, called a barycentric-space weighted tractography (B WT) algorithm, was shown to improve streamline tracking technique (STT) algorithms used for creating m,ultiple connection fiber trajectories for branching and crossing. Considering the weight of diffusion anisotropy in the current and surrounding voxels, and the fact that the direction of income vector and the principal eigenvector had only a small bias towards the direction of surrounding voxels, the algorithm performed well. This was largely due to the application of m,ultiple seeds and bidirectional tracing for each fiber. Fractional isotropy (FI) related to fractional anisotropy (FA) is proposed for the purpose of determining the threshold of separate brain tissues. The white matter region was used as a mask to reduce the number of seeds in order to increase the efficiency of the fiber tracking software. Synthetic and clinical diffusion tensor imaging (DTI) data were employed to demonstrate the effectiveness of the fiber tracking algorithm. The experimental results show that the fiber visualization is reasonable.