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.

Online Journal Article

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).

Professor of Radiology (Body Imaging) and, by courtesy, of Bioengineering
Associate Professor (Research) of Radiology (Radiological Sciences Laboratory)
Professor of Radiology (Radiological Sciences Laboratory) and, by courtesy, of Electrical Engineering and of Bioengineering
This profile is not available