Age and gender-related changes in choroidal thickness: Insights from deep learning analysis of swept-source OCT images.

Journal: Photodiagnosis and photodynamic therapy
PMID: 39900214

Abstract

BACKGROUND: The choroid is a vital vascular layer of the eye, essential for maintaining ocular health. Understanding its structural variations, particularly choroidal thickness (CT), is crucial for the early detection of diseases, such as age-related macular degeneration (AMD), high myopia (HM), and diabetes mellitus (DM). Recent advancements in deep learning have significantly improved the segmentation and measurement of choroidal layers.

Authors

  • Dan Song
    Department of Ophthalmology, Beijing Tisnghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
  • Guanzheng Wang
    Institute for Cognitive Neurodynamics, School of Science, East China University of Science and Technology, Meilong Road 130 Shanghai 200237, China.
  • Guangfeng Liu
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Chengxia Zhang
    Department of Ophthalmology, Peking University International Hospital, No.1 Shengmingyuan Road, Zhongguancun Life Science Park, Changping District, Beijing, PR China. Electronic address: zhangchengxia@pkuih.edu.cn.
  • Bin Lv
    Ping An Healthcare Technology, Shang Hai, PR China.
  • Yuan Ni
    IBM Research, China, Beijing, China.
  • Guotong Xie
    Ping An Health Technology, Beijing, China.

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