Multi-Shot DWI Reconstruction with Magnitude-Based Spatial-Angular Locally Low-Rank Regularization (SPA-LLR)
Acquisition of diffusion-weighted images along multiple directions is needed for deriving microstructural metrics from diffusion models, and may also provide valuable information for some clinical applications. In this work, we introduce a non-linear model that jointly reconstructs images from different diffusion-encoding directions. In this model, we separately reconstruct the magnitude and phase images so that we can directly apply a constraint (e.g., locally low-rank) on the magnitude images to utilize the angular correlations without being influenced by the motion-induced phase variations. We demonstrate the significantly reduced noise level by this joint reconstruction method in experiments with different resolutions, b-values, and numbers of diffusion-encoding directions. This method can also reduce the required numbers of diffusion-encoding directions to save scan time and is still able to utilize angular correlations.
Hu Y, Wang X, Tian Q, Yang G, Daniel B, McNab J, Hargreaves B. Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization (SPA-LLR). Magn Reson Med. 2020 May;83(5):1596-1607.
Figure depicting the construction of the spatial-angular matrix for reconstruction of multi-shot DWI data using magnitude-based spatial-angular locally low-rank regularization (SPA-LLR).



