Investigation of the Role of Convolutional Neural Network Architectures in the Diagnosis of Glaucoma using Color Fundus Photography.


Atalay E., Özalp O., Devecioğlu Ö. C., Erdoğan H., İnce T., Yıldırım N.

Turkish journal of ophthalmology, vol.52, no.3, pp.193-200, 2022 (Scopus) identifier identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 52 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.4274/tjo.galenos.2021.29726
  • Journal Name: Turkish journal of ophthalmology
  • Journal Indexes: Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.193-200
  • Keywords: Glaucoma, convolutional neural network, artificial intelligence, telemedicine, OPEN-ANGLE GLAUCOMA, MACHINE LEARNING CLASSIFIERS, VISION LOSS, PREVALENCE, DEEP, CLASSIFICATION, POPULATION, WORLDWIDE, CHINESE, IMAGES
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

Objectives: To evaluate the performance of convolutional neural network (CNN) architectures to distinguish eyes with glaucoma from normal eyes.