Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system.

Journal: PloS one
Published Date: Jun 17, 2025

Abstract

OBJECTIVE: This study aims to utilize artificial intelligence technology to conduct an in-depth analysis of fundus data from myopic children and adolescents, thoroughly exploring the correlation between retinal vascular parameters and axial length (AL), and ultimately revealing the changing patterns of retinal vascular characteristics in children with different refractive errors. The findings aim to provide a scientific basis for the prevention, early screening, and formulation of personalized treatment strategies for myopia.

Authors

  • Chaoyang Zhao
    Department of Cardiovascular Surgery, the Second Affiliated Hospital, Hainan Medical University, Haikou 570311, China.
  • Huilin Li
    Department of Ophthalmology, Heji Hospital Affiliated with Changzhi Medical College, Changzhi, China.
  • Ziyou Yuan
    Department of Ophthalmology, Heji Hospital Affiliated with Changzhi Medical College, Changzhi, China.
  • Zihan Yang
    Institute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-Scale Optical Information Science and Technology, Tianjin, 300350, China.
  • Tiantian Wang
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Qian Tong
    Department of Public Health and Preventive Medicine, Changzhi Medical College, Changzhi, Shanxi, China.
  • Shaofeng Hao
    Department of Ophthalmology, Heji Hospital Affiliated with Changzhi Medical College, Changzhi, China.

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