Research On Fiber Tracking Algorithm In Diffusion Tensor Imaging

Diffusion Tensor Imaging (DTI) is a fairly new Magnetic Resonance Imaging technique, which can be used to characterize the diffusion pattern of water molecules in tissue. The apparent diffusion coeffcient (ADC) is a measure for the diffusion. In structured tissue the ADC is direction dependent:it is larger in the direction along structures than in the directions perpendicular to it. The measurement of ADC by DTI involves solving an eigensystem problem:finding three eigenvalues and their corresponding eigenvectors of a diffusion tensor matrix, which is a3×3symmetric matrix established by MRI images acquired along six directions. The eigenvector with the largest eigenvalue corresponds to the main diffusion direction. The other two eigenvectors correspond to directions perpendicular to this direction.The task of fiber tracking lies in generating the water diffusion paths in brain through the use of diffusion tensor imaging (DTI) in magnetic resonance imaging (MRI) modality. The basic assumption of the fiber tracking technique includes two folds:1) water paths manifest as a fiber bundle, and 2) the fiber orientation corresponds to the major eigenvector of the diffusion tensor. To explore a technique for overcoming the obstacles discretized nerve fiber images and to find the most likely directions of nerve fibers, we presented a new robust fiber tracking algorithm in diffusion tensor imaging. The robustness lies in that it includes three situations and the joint utilization of the preference direction determined by tensor analysis, the fractional anisotropy value, and the previous propagation direction. The 3D Cyrus Beck algorithm is used to calculate the propagation points on the grid for next step.In implementation, we use six ADC datasets that were obtained from a healthy human brain by MRI. Each dataset is 3D array of 128×128×30. We have implemented the fiber tracking algorithm in the region of interest by Mathematica.As a result, this algorithm shows stronger potential to reliably depict the distribution of white matter fibers in human brain. Experimental demonstrations with MRI-DTI data are presented.