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 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.

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Publication Details

Journal
IEEE Access
Published
2024-12-25
DOI
https://doi.org/10.1109/access.2024.3522204
Citations
1
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.40

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

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

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article en
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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, higher temporal resolution, and over 5 times faster reconstruction speed than existing motion-corrected GRASP frameworks.

IEEE AccessVol. 13
Philips (Finland) (FI), University of Nottingham Ningbo China (CN), University of Nottingham (GB), COMSATS University Islamabad (PK), Philips (China) (CN)
National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 31%
Advanced MRI Techniques and Applications
0.40
DOIOpen Access PDFOpenAlex
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