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, cilt.52, sa.3, ss.193-200, 2022 (Scopus) identifier identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 52 Sayı: 3
  • Basım Tarihi: 2022
  • Doi Numarası: 10.4274/tjo.galenos.2021.29726
  • Dergi Adı: Turkish journal of ophthalmology
  • Derginin Tarandığı İndeksler: Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.193-200
  • Anahtar Kelimeler: Glaucoma, convolutional neural network, artificial intelligence, telemedicine, OPEN-ANGLE GLAUCOMA, MACHINE LEARNING CLASSIFIERS, VISION LOSS, PREVALENCE, DEEP, CLASSIFICATION, POPULATION, WORLDWIDE, CHINESE, IMAGES
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

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