Automatic fiber tractography from DTI and its validation

To understand evolving pathology in the central nervous system (CNS) and develop effective treatments, it is essential to correlate the nerve fiber connectivity with the visualization of function. Such information is fundamental in CNS processes since anatomical connections determine where information is passed and processed Diffusion tensor imaging (DTI) can provide the fundamental information required for viewing structural connectivity. However robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper we present a novel, algorithm for automatic fiber tract mapping in the CNS specifically, a rat spinal cord as well as validate the mapped fibers using ex-vivo fluoro images of the excised rat. The novelty of our work lies in the fiber tract mapping as well as the validation experiment. The automatic fiber tract mapping problem will be solved in two phases, namely a data smoothing phase and a fiber tract mapping phase. In the former smoothing is achieved via a new weighted TV-norm minimization which strives to smooth while retaining all relevant detail. For the fiber tract mapping, a smooth 3D vector field indicating the dominant anisotropic direction at each spatial location is computed from the smoothed data. Fiber tracts are then determined as the smooth integral curves of this vector field in a variational framework Examples are presented for DTI data sets from a normal and injured rat spinal cords respectively.