A New Method for Fiber Tractography in Diffusion Tensor Magnetic Resonance Images

This paper deals with the development of a new fiber tracking algorithm to be used with high resolution diffusion tensor fields acquired via magnetic resonance imaging. The tracking of white matter fibers in the human brain will improve the diagnosis and treatment of many neuronal diseases. The algorithm here proposed is based on a mixture of geometrical and probabilistic criteria. The method performs satisfactorily in regions with branching and crossing fibers and offers the capability of reporting a probability value for the computed tracts. This certainty figure takes into account both the anisotropy and the information provided by all the eigenvectors and eigenvalues of the diffusion matrix at each voxel.