QModeL: A plug-and-play model-based reconstruction for highly accelerated multi-shot diffusion MRI using learned priors.

ABSTRACT:

Purpose

To introduce a joint reconstruction method for highly undersampled multi-shot diffusion weighted (msDW) scans.

Methods

Multi-shot EPI methods enable higher spatial resolution for diffusion MRI, but at the expense of long scan-time. Highly accelerated msDW scans are needed to enable their utilization in advanced microstructure studies, which require high q-space coverage. Previously, joint k-q undersampling methods coupled with compressed sensing were shown to enable very high acceleration factors. However, the reconstruction of this data using sparsity priors is challenging and is not suited for multi-shell data. We propose a new reconstruction that recovers images from the combined k-q data jointly. The proposed qModeL reconstruction brings together the advantages o

SUBMITTER: Mani M 

PROVIDER: S-EPMC8076086 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature