Laser & Optoelectronics Progress, Volume. 61, Issue 12, 1211005(2024)

Reconstruction of Magnetic Resonance Imaging Based on Dual-Domain Densely-Connected Residual Convolutional Networks

Weikun Zhang1, Qiaohong Liu2、*, Xiaoxiang Han1, Yuanjie Lin1, and Keyan Chen1
Author Affiliations
  • 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
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    References(19)

    [9] Liu Y, Lu Z Y, Wang J et al. Gibbs artifact removal algorithm for magnetic resonance imaging based on self-attention connection UNet[J]. Journal of Computer Applications, 43, 1606-1611(2023).

    [14] Zhang D Q, Liu X H, Pang Y W. Magnetic resonance image reconstruction based on dual-domain parallel codec network[J]. Laser & Optoelectronics Progress, 59, 1210014(2022).

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    Weikun Zhang, Qiaohong Liu, Xiaoxiang Han, Yuanjie Lin, Keyan Chen. Reconstruction of Magnetic Resonance Imaging Based on Dual-Domain Densely-Connected Residual Convolutional Networks[J]. Laser & Optoelectronics Progress, 2024, 61(12): 1211005

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    Paper Information

    Category: Imaging Systems

    Received: Jun. 6, 2023

    Accepted: Aug. 22, 2023

    Published Online: Jun. 3, 2024

    The Author Email: Qiaohong Liu (hqllqh@163.com)

    DOI:10.3788/LOP231468

    CSTR:32186.14.LOP231468

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