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

Original languageEnglish
Pages (from-to)1867-1881
Number of pages15
JournalIEEE Access
Volume13
DOIs
Publication statusPublished - 2025

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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