Segmented diffusion imaging with iterative motion‐corrected reconstruction (SEDIMENT) for brain echo‐planar imaging. (9th December 2019)

• Record Type: Journal Article
• Authors: Steinhoff, Malte; Nehrke, Kay; Mertins, Alfred; Börnert, Peter
• Other Names: Spencer Richard G. guestEditor.
• Is Part Of: NMR in biomedicine. Volume 33:Number 12(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-09
• Subjects: brain -- EPI -- model‐based image reconstruction -- motion correction -- multi‐shot DWI -- SENSE; Nuclear magnetic resonance -- Periodicals; Magnetic Resonance Spectroscopy -- Periodicals; 574
• DOI: 10.1002/nbm.4185
• Languages: English
• ISSNs: 0952-3480

Abstract

Abstract: Multi‐shot techniques offer improved resolution and signal‐to‐noise ratio for diffusion‐ weighted imaging, but make the acquisition vulnerable to shot‐specific phase variations and inter‐shot macroscopic motion. Several model‐based reconstruction approaches with iterative phase correction have been proposed, but robust macroscopic motion estimation is still challenging. Segmented diffusion imaging with iterative motion‐corrected reconstruction (SEDIMENT) uses iteratively refined data‐driven shot navigators based on sensitivity encoding to cure phase and rigid in‐plane motion artifacts. The iterative scheme is compared in simulations and in vivo with a non‐iterative reference algorithm for echo‐planar imaging with up to sixfold segmentation. The SEDIMENT framework supports partial Fourier acquisitions and furthermore includes options for data rejection and learning‐based modules to improve robustness and convergence. Abstract : Multi‐shot diffusion‐weighted imaging is severely susceptible to motion‐induced shot variations caused by macroscopic subject motion and minuscule motion, the latter affecting foremost the signal phase. The presented SEDIMENT framework incorporates iterative physiological phase and macroscopic rigid in‐plane motion correction using SENSE‐based shot navigators. SEDIMENT achieves increased image‐quality compared to non‐iterative algorithms for echo‐planar brain imaging and, furthermore, smoothly includes iterative data rejection and symmetry constraints for partial Fourier acquisitions.