Deep learning-based automated classification of choroidal layers in en face swept-source optical coherence tomography images.

Journal: BMC ophthalmology
Published Date: Jul 1, 2025

Abstract

BACKGROUND: This study aims to develop a deep learning-based algorithm dedicated to the automated classification of choroidal layers in en face swept-source optical coherence tomography (SS-OCT) images of the eye.

Authors

  • Je Moon Yoon
    Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea.
  • Ji Young Lim
    Department of Artificial Intelligent, Sungkyunkwan University, 2066 seobu- ro, Jangan-gu, Suwon-si, 16419, Gyeonggi-do, Korea.
  • Hoon Noh
    Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • Seung Wan Nam
    Hangil Eye Hospital, 35 Bupyeong-daero, Bupyeong-gu, Incheon, 21388, Republic of Korea.
  • Jee-Hyong Lee
    Department of Artificial Intelligent, Sungkyunkwan University, 2066 seobu- ro, Jangan-gu, Suwon-si, 16419, Gyeonggi-do, Korea. john@skku.edu.
  • Don-Ll Ham
    Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea. oculus@naver.com.

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