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

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

doi:10.1109/ACCESS.2024.3522204

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

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

Research output: Journal Publication › Article › peer-review

Abstract

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 and higher reconstruction efficiency compared to existing motion-corrected GRASP frameworks.

Original language	English
Journal	IEEE Access
DOIs	https://doi.org/10.1109/ACCESS.2024.3522204
Publication status	Accepted/In press - 2024

Keywords

Compressed sensing
DCE-MRI
motion correction
parallel imaging
reconstruction efficiency
soft weighting

ASJC Scopus subject areas

General Computer Science
General Materials Science
General Engineering

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10.1109/ACCESS.2024.3522204

Cite this

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title = "Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank with Soft Weighting",

abstract = "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 and higher reconstruction efficiency compared to existing motion-corrected GRASP frameworks.",

keywords = "Compressed sensing, DCE-MRI, motion correction, parallel imaging, reconstruction efficiency, soft weighting",

author = "Jichang Zhang and Faisal Najeeb and Yulin Wang and Xinpei Wang and Pengfei Xu and Hammad Omer and Jianjun Zheng and Jingfeng Zhang and Sue Francis and Paul Glover and Richard Bowtell and Thomas Meersmann and Chengbo Wang",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2024",

doi = "10.1109/ACCESS.2024.3522204",

language = "English",

journal = "IEEE Access",

issn = "2169-3536",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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TY - JOUR

T1 - Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank with Soft Weighting

AU - Zhang, Jichang

AU - Najeeb, Faisal

AU - Wang, Yulin

AU - Wang, Xinpei

AU - Xu, Pengfei

AU - Omer, Hammad

AU - Zheng, Jianjun

AU - Zhang, Jingfeng

AU - Francis, Sue

AU - Glover, Paul

AU - Bowtell, Richard

AU - Meersmann, Thomas

AU - Wang, Chengbo

PY - 2024

Y1 - 2024

N2 - 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 and higher reconstruction efficiency compared to existing motion-corrected GRASP frameworks.

AB - 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 and higher reconstruction efficiency compared to existing motion-corrected GRASP frameworks.

KW - Compressed sensing

KW - DCE-MRI

KW - motion correction

KW - parallel imaging

KW - reconstruction efficiency

KW - soft weighting

UR - http://www.scopus.com/inward/record.url?scp=85213284053&partnerID=8YFLogxK

U2 - 10.1109/ACCESS.2024.3522204

DO - 10.1109/ACCESS.2024.3522204

M3 - Article

AN - SCOPUS:85213284053

SN - 2169-3536

JO - IEEE Access

JF - IEEE Access

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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