Fractional anisotropy-weighted front evolution algorithm for white matter tractography based on diffusion tensor imaging data
Tractography is one of the most important applications of diffusion tensor imaging (DTI) which noninvasively reconstructs 3D trajectories of the white matter tracts. Because of the intravoxel orientation heterogeneity of DTI data, some of tractography algorithms are unable to follow the correct pathways after the crossing and branching regions. Front propagation techniques are efficient methods in tracking the crossing fibers. A key parameter influencing the performance of these algorithms is the cost function which is mainly based on the colinearity of tensors' eigenvectors. The effect of the eigenvalues on the anisotropy strength of tensor has not been previously addressed in the definition of the speed function. In this article, a new speed function, based on the effect of diffusion anisotropy and the colinearity of eigenvectors is proposed. The performance of the suggested method on fiber tracking and crossing fiber detection has been evaluated using synthetic datasets, and the feasibility of the proposed method was shown by fiber tracking implemented on real DTI data.  2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 307314, 2011
white matter tractography diffusion tensor imaging front propagation fast marching algorithm fractional anisotropy adaptive fractional anisotropy-weighted speed function fiber crossing