Recognition of eye diseases based on deep neural networks for transfer learning and improved D-S evidence theory.

Journal: BMC medical imaging
Published Date: Jan 18, 2024

Abstract

BACKGROUND: Human vision has inspired significant advancements in computer vision, yet the human eye is prone to various silent eye diseases. With the advent of deep learning, computer vision for detecting human eye diseases has gained prominence, but most studies have focused only on a limited number of eye diseases.

Authors

  • Fanyu Du
    School of Medical Imaging, North Sichuan Medical College, Nanchong, 637000, China.
  • Lishuai Zhao
    School of Medical Imaging, North Sichuan Medical College, Nanchong, 637000, China.
  • Hui Luo
    Thoracic Surgery Department, Nan Chong Center Hospital, Nanchong, China.
  • Qijia Xing
    Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China.
  • Jun Wu
    Department of Emergency, Zhuhai Integrated Traditional Chinese and Western Medicine Hospital, Zhuhai, 519020, Guangdong Province, China. quanshabai43@163.com.
  • Yuanzhong Zhu
    School of Medical Imaging, North Sichuan Medical College, Nanchong, 637000, China.
  • Wansong Xu
    School of Medical Imaging, North Sichuan Medical College, Nanchong, 637000, China.
  • Wenjing He
    Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Ophthalmology Department, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
  • Jianfang Wu
    Faculty of Data Science, City University of Macau, Macau, 999078, China. wujianfang314@gmail.com.

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