Distribution and determinants of choroidal vascularity index in healthy eyes from deep-learning choroidal analysis: a population-based SS-OCT study.

Journal: The British journal of ophthalmology
Published Date:

Abstract

AIMS: To quantify the profiles of choroidal vascularity index (CVI) using fully artificial intelligence (AI)-based algorithm applied to swept-source optical coherence tomography (SS-OCT) images and evaluate the determinants of CVI in a population-based study.

Authors

  • Meng Xuan
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China.
  • Cong Li
    Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science, National Demonstration Center for Experimental Chemistry Education, Northwest University, Xi'an, Shaanxi 710127, China. Electronic address: licong@nwu.edu.cn.
  • Xiangbin Kong
    Department of Ophthalmology, Affiliated Foshan Hospital, Southern Medical University, Foshan, Guangdong, China.
  • Jian Zhang
    College of Pharmacy, Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Mingguang He
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, China; Centre for Eye Research Australia; Departments of Ophthalmology and Surgery, University of Melbourne, Melbourne, Australia. Electronic address: mingguang.he@unimelb.edu.au.