Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization (SPA-LLR).

PURPOSE

To resolve the motion-induced phase variations in multi-shot multi-direction diffusion-weighted imaging (DWI) by applying regularization to magnitude images.

THEORY AND METHODS

A nonlinear model was developed to estimate phase and magnitude images separately. A locally low-rank regularization (LLR) term was applied to the magnitude images from all diffusion-encoding directions to exploit the spatial and angular correlation. In vivo experiments with different resolutions and b-values were performed to validate the proposed method.

RESULTS

The proposed method significantly reduces the noise level compared to the conventional reconstruction method and achieves submillimeter (0.8mm and 0.9mm isotropic resolutions) DWI with a b-value of 1,000  and 1-mm isotropic DWI with a b-value of 2,000  without modification of the sequence.

CONCLUSIONS

A joint reconstruction method with spatial-angular LLR regularization on magnitude images substantially improves multi-direction DWI reconstruction, simultaneously removes motion-induced phase artifacts, and denoises images.