Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS)

Merry Mani; Mathews Jacob; Douglas Kelley; Vincent Magnotta

doi:10.1002/mrm.26382

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Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS)

Journal article

Peer reviewed

Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS)

Merry Mani, Mathews Jacob, Douglas Kelley and Vincent Magnotta

Magnetic resonance in medicine, Vol.78(2), pp.494-507

08/2017

DOI: 10.1002/mrm.26382

PMCID: PMC5336529

PMID: 27550212

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https://www.ncbi.nlm.nih.gov/pmc/articles/5336529View

Open Access

Abstract

To introduce a novel method for the recovery of multi-shot diffusion weighted (MS-DW) images from echo-planar imaging (EPI) acquisitions. Current EPI-based MS-DW reconstruction methods rely on the explicit estimation of the motion-induced phase maps to recover artifact-free images. In the new formulation, the k-space data of the artifact-free DWI is recovered using a structured low-rank matrix completion scheme, which does not require explicit estimation of the phase maps. The structured matrix is obtained as the lifting of the multi-shot data. The smooth phase-modulations between shots manifest as null-space vectors of this matrix, which implies that the structured matrix is low-rank. The missing entries of the structured matrix are filled in using a nuclear-norm minimization algorithm subject to the data-consistency. The formulation enables the natural introduction of smoothness regularization, thus enabling implicit motion-compensated recovery of the MS-DW data. Our experiments on in-vivo data show effective removal of artifacts arising from inter-shot motion using the proposed method. The method is shown to achieve better reconstruction than the conventional phase-based methods. We demonstrate the utility of the proposed method to effectively recover artifact-free images from Cartesian fully/under-sampled and partial Fourier acquired data without the use of explicit phase estimates. Magn Reson Med 78:494-507, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Brain - diagnostic imaging

Algorithms

Humans

Signal Processing, Computer-Assisted

Adult

Image Processing, Computer-Assisted - methods

Diffusion Magnetic Resonance Imaging - methods

Echo-Planar Imaging

Details

Title: Subtitle: Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS)
Creators: Merry Mani - Department of Psychiatry, University of Iowa, Iowa City, Iowa, USA
Mathews Jacob - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA
Douglas Kelley - GE Healthcare
Vincent Magnotta - Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
Resource Type: Journal article
Publication Details: Magnetic resonance in medicine, Vol.78(2), pp.494-507
DOI: 10.1002/mrm.26382
PMID: 27550212
PMCID: PMC5336529
NLM abbreviation: Magn Reson Med
ISSN: 0740-3194
eISSN: 1522-2594
Publisher: United States
Grant note: T32 MH019113 / NIMH NIH HHS P30 CA086862 / NCI NIH HHS R01 EB019961 / NIBIB NIH HHS
Language: English
Date published: 08/2017
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Psychiatry; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984051768302771

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