Yuxin Hu1,2, Xiaole Wang1, Qiyuan Tian1,2, Grant Yang1,2, Bruce Daniel2,3, Jennifer McNab2, Brian Hargreaves1,2,3. 1. Department of Electrical Engineering, Stanford University, Stanford, California. 2. Department of Radiology, Stanford University, Stanford, California. 3. Department of Bioengineering, Stanford University, Stanford, California.
Abstract
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 s / mm 2 and 1-mm isotropic DWI with a b-value of 2,000 s / mm 2 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.
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 s / mm 2 and 1-mm isotropic DWI with a b-value of 2,000 s / mm 2 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.
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