Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting

This paper introduces a motion-corrected, free-breathing dynamic contrast-enhanced (DCE) MRI reconstruction method, termed low-rank plus sparse (L+S) with soft weighting. We designed a soft weighting matrix that smoothly transitions spokes between the target and other motion states to suppress motio...

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Main Authors: Jichang Zhang, Faisal Najeeb, Yulin Wang, Xinpei Wang, Pengfei Xu, Hammad Omer, Jianjun Zheng, Jingfeng Zhang, Sue Francis, Paul Glover, Richard Bowtell, Thomas Meersmann, Chengbo Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10813163/
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author Jichang Zhang
Faisal Najeeb
Yulin Wang
Xinpei Wang
Pengfei Xu
Hammad Omer
Jianjun Zheng
Jingfeng Zhang
Sue Francis
Paul Glover
Richard Bowtell
Thomas Meersmann
Chengbo Wang
author_facet Jichang Zhang
Faisal Najeeb
Yulin Wang
Xinpei Wang
Pengfei Xu
Hammad Omer
Jianjun Zheng
Jingfeng Zhang
Sue Francis
Paul Glover
Richard Bowtell
Thomas Meersmann
Chengbo Wang
author_sort Jichang Zhang
collection DOAJ
description This paper introduces a motion-corrected, free-breathing dynamic contrast-enhanced (DCE) MRI reconstruction method, termed low-rank plus sparse (L+S) with soft weighting. We designed a soft weighting matrix that smoothly transitions spokes between the target and other motion states to suppress motion blurring. The optimized fast iterative shrinkage-thresholding algorithm (FISTA) was employed to solve the L+S optimization problem, enabling faster convergence and better image quality. A DCE-MRI computer simulation framework, based on a modified Shepp-Logan model, was used as ground truth to quantify the motion suppression errors. Both simulation and clinical datasets demonstrate that the proposed method provides superior motion correction, higher temporal resolution, and over 5 times faster reconstruction speed than existing motion-corrected GRASP frameworks.
format Article
id doaj-art-960ee89a47484befb8cd0167bec4b606
institution Kabale University
issn 2169-3536
language English
publishDate 2025-01-01
publisher IEEE
record_format Article
series IEEE Access
spelling doaj-art-960ee89a47484befb8cd0167bec4b6062025-01-16T00:01:48ZengIEEEIEEE Access2169-35362025-01-01131867188110.1109/ACCESS.2024.352220410813163Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft WeightingJichang Zhang0https://orcid.org/0000-0002-3958-5152Faisal Najeeb1https://orcid.org/0000-0002-7709-6915Yulin Wang2Xinpei Wang3Pengfei Xu4https://orcid.org/0000-0002-7095-8535Hammad Omer5Jianjun Zheng6Jingfeng Zhang7Sue Francis8Paul Glover9https://orcid.org/0000-0002-5694-1470Richard Bowtell10https://orcid.org/0000-0001-8656-412XThomas Meersmann11Chengbo Wang12Faculty of Science and Engineering, University of Nottingham, Ningbo, ChinaDepartment of Electrical and Computer Engineering, MIPRG Research Group, COMSATS University Islamabad, Islamabad, PakistanFaculty of Science and Engineering, University of Nottingham, Ningbo, ChinaPhilips Healthcare Technology (China) Company, Suzhou Branch, Suzhou, ChinaHebei Key Laboratory of Intelligent Data Information Processing and Control, Tangshan University, Tangshan, ChinaDepartment of Electrical and Computer Engineering, MIPRG Research Group, COMSATS University Islamabad, Islamabad, PakistanNingbo Clinical Medical Research Center of Imaging Medicine, Ningbo, ChinaNingbo Clinical Medical Research Center of Imaging Medicine, Ningbo, ChinaSir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, U.KSir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, U.KSir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, U.KSir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, U.KFaculty of Science and Engineering, University of Nottingham, Ningbo, ChinaThis paper introduces a motion-corrected, free-breathing dynamic contrast-enhanced (DCE) MRI reconstruction method, termed low-rank plus sparse (L+S) with soft weighting. We designed a soft weighting matrix that smoothly transitions spokes between the target and other motion states to suppress motion blurring. The optimized fast iterative shrinkage-thresholding algorithm (FISTA) was employed to solve the L+S optimization problem, enabling faster convergence and better image quality. A DCE-MRI computer simulation framework, based on a modified Shepp-Logan model, was used as ground truth to quantify the motion suppression errors. Both simulation and clinical datasets demonstrate that the proposed method provides superior motion correction, higher temporal resolution, and over 5 times faster reconstruction speed than existing motion-corrected GRASP frameworks.https://ieeexplore.ieee.org/document/10813163/Compressed sensingDCE-MRImotion correctionparallel imagingreconstruction efficiencysoft weighting
spellingShingle Jichang Zhang
Faisal Najeeb
Yulin Wang
Xinpei Wang
Pengfei Xu
Hammad Omer
Jianjun Zheng
Jingfeng Zhang
Sue Francis
Paul Glover
Richard Bowtell
Thomas Meersmann
Chengbo Wang
Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting
IEEE Access
Compressed sensing
DCE-MRI
motion correction
parallel imaging
reconstruction efficiency
soft weighting
title Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting
title_full Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting
title_fullStr Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting
title_full_unstemmed Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting
title_short Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting
title_sort improved motion correction in dynamic contrast enhanced mri using low rank with soft weighting
topic Compressed sensing
DCE-MRI
motion correction
parallel imaging
reconstruction efficiency
soft weighting
url https://ieeexplore.ieee.org/document/10813163/
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