Super Resolution Reconstruction from Differently Oriented Diffusion Tensor Datasets

Gwendolyn Van Steenkiste¹, Ben Jeurissen¹, Jan Sijbers¹, Dirk H.J. Poot²

Diffusion MRI typically employs large voxels to obtain sufficiently high SNR. Given the large voxel sizes, many voxels consist of a mixture of signals from different anatomical structures. To reduce the partial volume effect and retain high SNR, we propose a super resolution acquisition and reconstruction technique that directly computes high SNR and high resolution DTI parameters from a set of low resolution diffusion MRI data sets. Using simulations we show our technique outperforms direct high resolution acquisition and current super resolution reconstruction techniques which don't take into account the underlying diffusion model.