Enhancing pathological myopia diagnosis: a bimodal artificial intelligence approach integrating fundus and optical coherence tomography imaging for precise atrophy, traction and neovascularisation grading.

Journal: The British journal of ophthalmology
Published Date: May 20, 2025

Abstract

BACKGROUND: Pathological myopia (PM) has emerged as a leading cause of global visual impairment, early detection and precise grading of PM are crucial for timely intervention. The atrophy, traction and neovascularisation (ATN) system is applied to define PM progression and stages with precision. This study focuses on constructing a comprehensive PM image dataset comprising both fundus and optical coherence tomography (OCT) images and developing a bimodal artificial intelligence (AI) classification model for ATN grading in PM.

Authors

  • Zhiyan Xu
    Department of Ophthalmology, Peking Union Medical College Hospital, Dongcheng District, Beijing, China.
  • Yajie Yang
    Vistel AI Lab, Visionary Intelligence LTD, Beijing, China.
  • Huan Chen
    Beijing Guangqumen Middle School, Beijing, 100062, China.
  • Ruo'an Han
    Department of Ophthalmology, Peking Union Medical College Hospital, Beijing, China.
  • Xiaoxu Han
    Department of Ophthalmology, Union Medical College Hospital, Chinese Academy of Medical Sciences, PekingBeijing, China.
  • Jianchun Zhao
    Vistel AI Lab, Visionary Intelligence Ltd, Beijing, China.
  • Weihong Yu
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China yuweihongpumch@163.com.
  • Zhikun Yang
    Department of Ophthalmology, Peking Union Medical College Hospital, Dongcheng District, 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.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals