Optical Instruments, Volume. 46, Issue 6, 64(2024)

OCT retinal images super-resolution reconstruction based on PSRGAN and transfer learning

Minghui CHEN1, Shiyi XU1, Shuting KE1, Yi SHAO2, and Yuquan WU1
Author Affiliations
  • 1Shanghai Engineering Research Center of Interventional Medical Device , University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2Department of Urology, Shanghai General Hospital, Shanghai 200080, China
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    References(19)

    [4] [4] LEDIG C, THEIS L, HUSZÁR F, et al. Photorealistic single image superresolution using a generative adversarial wk[C]2017 IEEE Conference on Computer Vision Pattern Recognition. Honolulu: IEEE, 2017: 105 − 114.

    [8] UMEHARA K, OTA J, ISHIDA T. Application of super-resolution convolutional neural network for enhancing image resolution in chest CT[J]. Computers in Biology and Medicine, 31, 441-450(2018).

    [14] [14] WANG Q L, WU B G, ZHU P F, et al. ECA: efficient channel attention f deep convolutional neural wks[C]2020 IEEECVF Conference on Computer Vision Pattern Recognition (CVPR). Seattle, WA, USA: IEEE, 2020: 11531 − 11539.

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    Minghui CHEN, Shiyi XU, Shuting KE, Yi SHAO, Yuquan WU. OCT retinal images super-resolution reconstruction based on PSRGAN and transfer learning[J]. Optical Instruments, 2024, 46(6): 64

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    Paper Information

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    Received: Jan. 24, 2024

    Accepted: --

    Published Online: Jan. 21, 2025

    The Author Email:

    DOI:10.3969/j.issn.1005-5630.202401240011

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