Grading of diabetic retinopathy using a pre-segmenting deep learning classification model: Validation of an automated algorithm.

Journal: Acta ophthalmologica
Published Date: Oct 19, 2024

Abstract

PURPOSE: To validate the performance of autonomous diabetic retinopathy (DR) grading by comparing a human grader and a self-developed deep-learning (DL) algorithm with gold-standard evaluation.

Authors

  • Dyllan Edson Similié
    Department of Ophthalmology, Odense University Hospital, Odense, Denmark.
  • Jakob K H Andersen
    Steno Diabetes Center Odense, Odense, Denmark; SDU Robotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense, Denmark.
  • Sebastian Dinesen
    Department of Ophthalmology, Odense University Hospital, Odense, Denmark.
  • Thiusius R Savarimuthu
    SDU Robotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense, Denmark.
  • Jakob Grauslund
    Department of Ophthalmology, Odense University Hospital, Odense, Denmark; Research Unit of Ophthalmology, Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; Steno Diabetes Center Odense, Odense, Denmark. Electronic address: jakob.grauslund@rsyd.dk.

Keywords

External Resources

Popular Topics
Recent Journals