Development and quantitative assessment of deep learning-based image enhancement for optical coherence tomography.

Journal: BMC ophthalmology
Published Date: Mar 26, 2022

Abstract

PURPOSE: To develop a deep learning-based framework to improve the image quality of optical coherence tomography (OCT) and evaluate its image enhancement effect with the traditional image averaging method from a clinical perspective.

Authors

  • Xinyu Zhao
    AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA.
  • Bin Lv
    Ping An Healthcare Technology, Shang Hai, PR China.
  • Lihui Meng
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China.
  • Xia Zhou
    School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, 541004, China. Electronic address: xiazhou201612@guet.edu.cn.
  • Dongyue Wang
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China.
  • Wenfei Zhang
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China.
  • Erqian Wang
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China.
  • Chuanfeng Lv
    Ping An Healthcare Technology, Shang Hai, PR China.
  • Guotong Xie
    Ping An Health Technology, Beijing, China.
  • Youxin Chen
    Department of Ophthalmology Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences Beijing People's Republic of China.

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