Multi-band- and in-plane-accelerated diffusion MRI enabled by model-based deep learning in q-space and its extension to learning in the spherical harmonic domain.

ABSTRACT:

Purpose

To propose a new method for the recovery of combined in-plane- and multi-band (MB)-accelerated diffusion MRI data.

Methods

Combining MB acceleration with in-plane acceleration is crucial to improve the time efficiency of high (angular and spatial) resolution diffusion scans. However, as the MB factor and in-plane acceleration increase, the reconstruction becomes challenging due to the heavy aliasing. The new reconstruction utilizes an additional q-space prior to constrain the recovery, which is derived from the previously proposed qModeL framework. Specifically, the qModeL prior provides a pre-learned representation of the diffusion signal space to which the measured data belongs. We show that the pre-learned q-space prior along with a model-based iterative reconstru

SUBMITTER: Mani M 

PROVIDER: S-EPMC8855531 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature