Deep learning-based automatic image quality assessment in ultra-widefield fundus photographs.

Journal: BMJ open
Published Date: May 21, 2025

Abstract

OBJECTIVE: With a growing need for ultra-widefield fundus (UWF) fundus photographs in clinics and AI development, image quality assessment (IQA) of UWF fundus photographs is an important preceding step for accurate diagnosis and clinical interpretation. This study developed deep learning (DL) models for automated IQA of UWF fundus photographs (UWF-IQA model) and investigated intergrader agreements in the IQA of UWF fundus photographs.

Authors

  • Richul Oh
    Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea .
  • Un Chul Park
  • Kyu Hyung Park
    Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
  • Sang Jun Park
    Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
  • Chang Ki Yoon

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