High Angular Resolution Diffusion Image Registration

Diffusion Tensor Imaging (DTI) is a commonmethod for the investigation of brain white matter. In thismethod, it is assumed that diffusion of water molecules isGaussian and so, it fails in fiber crossings where this assumptiondoes not hold. High Angular Resolution Diffusion Imaging(HARDI) allows more accurate investigation of microstructuresof the brain white matter; it can present fiber crossing in eachvoxel. HARDI contains complex orientation information of thefibers. Therefore, registration of these images is morecomplicated than the scalar images. In this paper, we propose aHARDI registration algorithm based on the feature vectors thatare extracted from the Orientation Distribution Functions(ODFs) in each voxel. Hammer similarity measure is used tomatch the feature vectors and thin-plate spline (TPS) basedregistration is used for spatial registration of the skeleton and itsneighbors. A re-orientation strategy is utilized to re-orient theODFs after spatial registration. Finally, we evaluate our methodbased on the differences in principal diffusion direction and wewill show that utilizing the skeleton as landmark in theregistration results in accurate alignment of HARDI data.

Keywords:

high angular resolution diffusion imaging HARDI) , Q-ball imaging , orientation distribution function (ODF) , registration , principal diffusion direction (PDD)