Laser & Optoelectronics Progress, Volume. 59, Issue 22, 2217001(2022)

Super-Resolution Reconstruction of Magnetic Resonance Image Based on Deep Learning

Mengxue Pan, Ning Qu, Yeru Xia, Deyong Yang, Hongyu Wang, and Wenlong Liu*
Author Affiliations
  • Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China
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    References(19)

    [3] Xiao K, Tian L J, Wang Z Y. Fast super-resolution fluorescence microscopy imaging with low signal-to-noise ratio based on deep learning[J]. Chinese Journal of Lasers, 47, 1007002(2020).

    [4] Hu F, Lin Y, Hou M D et al. Super-resolution reconstruction of cytoskeleton image based on deep learning[J]. Acta Optica Sinica, 40, 2410001(2020).

    [6] Wu L, Lü G Q, Xue Z T et al. Super-resolution reconstruction of images based on multi-scale recursive network[J]. Acta Optica Sinica, 39, 0610001(2019).

    [7] Peng Y F, Gao Y, Du T T et al. Single image super-resolution reconstruction method for generative adversarial network[J]. Journal of Frontiers of Computer Science and Technology, 14, 1612-1620(2020).

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    Mengxue Pan, Ning Qu, Yeru Xia, Deyong Yang, Hongyu Wang, Wenlong Liu. Super-Resolution Reconstruction of Magnetic Resonance Image Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2217001

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    Paper Information

    Category: Medical Optics and Biotechnology

    Received: Aug. 2, 2021

    Accepted: Oct. 13, 2021

    Published Online: Oct. 13, 2022

    The Author Email: Wenlong Liu (liuwl@dlut.edu.cn)

    DOI:10.3788/LOP202259.2217001

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