Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction.

ABSTRACT:

Purpose

To introduce a combined machine learning (ML)- and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI) and demonstrate its application in high-resolution structural and diffusion imaging.

Methods

Single-shot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging because of severe distortion artifacts and blurring. Although msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image. We utilize deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase va

SUBMITTER: Bilgic B 

PROVIDER: S-EPMC6626584 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature