A curvature deviation minimization searching method for MR diffusion tensor tractography

Recently, magnetic resonance diffusion tensor imaging (MR-DTI) has been used to analyze the structure and the function of the human brain. MR-DTI is a noninvasive method of measuring the diffusion phenomenon of water molecules in vivo. Tractographies using MR-DTI give the information of nerve fibers. They are promising for diagnoses of the disorder that has abnormalities in cerebral nerve fibers and analyses of functional connectivity among activated areas. In general, tractographies are able to track nerve fibers between near areas. However, it is difficult to track nerve fibers between distant areas due to partial volume effect in nerve fiber crossing areas. In this paper, we proposed a new tractography by searching minimum curvature deviation in fiber crossing areas using the trajectory of before and after the crossing areas. First, the method was evaluated by simulation images that illustrate the bilateral visual cortex through the corpus callosum. Subsequently, the method was applied to the real data. The results demonstrate the usefulness of the proposed method. (author)