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In neuroscience, tractography is a 3D modeling technique used to visually represent neural tracts using data collected by diffusion tensor imaging (DTI). It uses special techniques of magnetic resonance imaging (MRI), and computer-based image analysis. The results are presented in two- and three-dimensional images. In addition to the long tracts that connect the brain to the rest of the body, there are complicated neural networks formed by short connections among different cortical and subcortical regions. The existence of these bundles has been revealed by histochemistry and biological techniques on post-mortem specimens. Brain tracts are not identifiable by direct exam, CT, or MRI scans. This difficulty explains the paucity of their description in neuroanatomy atlases and the poor understanding of their functions. The MRI sequences used look at the symmetry of brain water diffusion. Bundles of fiber tracts make the water diffuse asymmetrically in a tensor, the major axis parallel to the direction of the fibers. The asymmetry here is called anisotropy. There is a direct relationship between the number of fibers and the degree of anisotropy. Figure legend: Diffusion tensor imaging (DTI) data have been used to seed various tractographic assessments of this patient's brain. These are seen in superior (A), posterior (B), and lateral views (C&D). The seeds have been used to develop arcuate and superior longitudinal fasciculi in (A) and (B), for brainstem, and corona radiata in (C), and as combined data sets in (D). Some of the two dimensional projections of the tractographic result are also shown. The data set may be rotated continuously into various planes to better appreciate the structure. Color has been assigned based on the dominant direction of the fibers. There is asymmetry in the tractographic fiber volume between the right and left arcuate fasciculus (Raf & Laf) (smaller on the left) and between the right and left superior longitudinal fasciculus (Rslf & Lslf) (smaller on the right). Also seen are Tapetum (Ta), Left corona radiata (Lcr) and Left middle cerebellar peduncle (Lmcp). == Mathematics == Using diffusion tensor MRI, one can measure the apparent diffusion coefficient at each voxel in the image, and after multilinear regression across multiple images, the whole diffusion tensor can be reconstructed. Suppose there is a fiber tract of interest in the sample. Following the Frenet–Serret formulas, we can formulate the space-path of the fiber tract as a parametrized curve: : where is the tangent vector of the curve. The reconstructed diffusion tensor can be treated as a matrix, and we can easily compute its eigenvalues and eigenvectors . By equating the eigenvector corresponding to the largest eigenvalue with the direction of the curve: : we can solve for given the data for . This can be done using numerical integration, e.g., using Runge-Kutta, and by interpolating the principal eigenvectors. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「tractography」の詳細全文を読む スポンサード リンク
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