Related Experiment Video
Updated: Jan 6, 2026
Diffusion Imaging in the Rat Cervical Spinal Cord
Published on: April 7, 2015
Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization
Yuxin Hu1,2, Xiaole Wang1, Qiyuan Tian1,2
1Department of Electrical Engineering, Stanford University, Stanford, California.
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.
