Automated segmentation of ultra-widefield fluorescein angiography of diabetic retinopathy using deep learning.

Journal: The British journal of ophthalmology
PMID: 36241374

Abstract

BACKGROUND/AIMS: Retinal capillary non-perfusion (NP) and neovascularisation (NV) are two of the most important angiographic changes in diabetic retinopathy (DR). This study investigated the feasibility of using deep learning (DL) models to automatically segment NP and NV on ultra-widefield fluorescein angiography (UWFA) images from patients with DR.

Authors

  • Phil-Kyu Lee
    Department of Ophthalmology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Bucheon, Republic of Korea.
  • Ho Ra
    Department of Ophthalmology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Gyeonggi-do, Republic of Korea.
  • Jiwon Baek
    Department of Ophthalmology, Bucheon St Mary's Hospital, College of Medicine, The Catholic University of Korea, Gyeonggi-do, Republic of Korea md.jiwon@gmail.com.

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