Laser & Optoelectronics Progress, Volume. 59, Issue 6, 0617017(2022)

Automatic Detection of Retinal Diseases Based on Lightweight Convolutional Neural Network

Lingxiao Wang1, Jun Yang1, Wensai Wang1, and Ting Li1,2、*
Author Affiliations
  • 1Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Tianjin 300192, China
  • 2Chinese Institute for Brain Research, Beijing, Beijing 102206, China
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    References(23)

    [6] Huang Q, Xia L K. Comparison of central corneal thicknesses measured with anterior segment optical coherence tomography and ultrasound pachymetry[J]. Chinese Journal of Laser Medicine & Surgery, 27, 370-374(2018).

    [13] Lian C M, Zhong S C, Zhang T F et al. Transfer learning-based classification of optical coherence tomography retinal images[J]. Laser & Optoelectronics Progress, 58, 011702(2021).

    [23] Zhang T F, Zhong S C, Lian C M et al. Retina image classification based on deep learning feature union[J]. Laser & Optoelectronics Progress, 57, 241025(2020).

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    Lingxiao Wang, Jun Yang, Wensai Wang, Ting Li. Automatic Detection of Retinal Diseases Based on Lightweight Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2022, 59(6): 0617017

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    Paper Information

    Category: Medical Optics and Biotechnology

    Received: Jan. 13, 2022

    Accepted: Feb. 10, 2022

    Published Online: Mar. 8, 2022

    The Author Email: Ting Li (liting@bme.cams.cn)

    DOI:10.3788/LOP202259.0617017

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