An improved low‐rank plus sparse unrolling network method for dynamic magnetic resonance imaging

The improved reconstruction performance demonstrates that our proposed time correlation modeling is simple and effective for accelerating MRI reconstruction. We hope our approach can serve as a reference for future research in dynamic MRI reconstruction.

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Publication Details

Journal
Medical Physics
Published
2024-11-28
DOI
https://doi.org/10.1002/mp.17501
Citations
4
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
1.62
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article

An improved low‐rank plus sparse unrolling network method for dynamic magnetic resonance imaging

Mingfeng Jiang, Zihan Yuan, Dong Ruan, Jucheng Zhang et al.
4 citations
Medical Physics
Advanced MRI Techniques and Applications
1.62
article

An improved low‐rank plus sparse unrolling network method for dynamic magnetic resonance imaging

Mingfeng Jiang, Zihan Yuan, Dong Ruan, Jucheng Zhang, Y Chen, Ling Xia
article en
4 citations

Abstract

The improved reconstruction performance demonstrates that our proposed time correlation modeling is simple and effective for accelerating MRI reconstruction. We hope our approach can serve as a reference for future research in dynamic MRI reconstruction.

Medical PhysicsVol. 52(1)
Zhejiang Sci-Tech University (CN), Second Affiliated Hospital of Zhejiang University (CN), Zhejiang University (CN)
Openalex Percentile: Top 15%
Advanced MRI Techniques and Applications
1.62
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