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

OBJECTIVES: To evaluate the performance of convolutional neural network (CNN) architectures to distinguish eyes with glaucoma from normal eyes. MATERIALS AND METHODS: A total of 9,950 fundus photographs of 5,388 patients from the database of Eskişehir Osmangazi University Faculty of Medicine Ophthal...

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Detalles Bibliográficos
Autores principales: Atalay, Eray, Özalp, Onur, Devecioğlu, Özer Can, Erdoğan, Hakika, İnce, Türker, Yıldırım, Nilgün
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Galenos Publishing 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249112/
https://www.ncbi.nlm.nih.gov/pubmed/35770344
http://dx.doi.org/10.4274/tjo.galenos.2021.29726

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249112/
https://www.ncbi.nlm.nih.gov/pubmed/35770344
http://dx.doi.org/10.4274/tjo.galenos.2021.29726

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