White matter connectivity by diffusion distance on 3T MRI

Diffusion tensor imaging (DTI) has become a powerful tool for analyzing the structure of while matter. We have already developed a novel method to assess white matter connectivity using diffusion tensor distance between neighborhood voxels. Diffusion tensor distance is defined as the length from the center to the surface of the diffusion tensor. In the proposed method, we use directional diffusion measurements to infer regional white matter connectivity. To assess the connectivity, we compose the map based on the projected tensor distance, then we put a label on the constructed map and segment regionally connected white matter using labels. We also apply the method to in vivo brain measurements at 3T MRI. Using the iterative algorithm, we can segment typical white matter trajectories such as corpus callosum. Compared with other algorithms using eigenvalues of the diffusion tensor, our approach has flexibility in selecting connected regions by using basic characteristics of the diffusion tensor shape. The purpose of this study is to obtain a quantitative map of white matter connectivity in vivo using diffusion tensor properties.