Inference of multiple fiber orientations in high angular resolution diffusion imaging

Abstract

A method is presented that is capable of determining more than one fiber orientation within a single voxel in high angular resolution diffusion imaging (HARDI) data sets. This method is an extension of the Markov chain method recently introduced to diffusion tensor imaging (DTI) analysis, allowing the probability density function of up to 2 intra-voxel fiber orientations to be inferred. The multiple fiber architecture within a voxel is then assessed by calculating the relative probabilities of a 1 and 2 fiber model. It is demonstrated that for realistic signal to noise ratios, it is possible to accurately characterize the directions of 2 intersecting fibers using a 2 fiber model. The shortcomings of under-fitting a 2 fiber model, or over-fitting a 1 fiber model, are explored. This new algorithm enhances the tools available for fiber tracking. © 2005 Wiley-Liss, Inc.