Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography

PURPOSE: To evaluate the role of ensemble learning techniques with deep learning in classifying diabetic retinopathy (DR) in optical coherence tomography angiography (OCTA) images and their corresponding co-registered structural images. METHODS: A total of 463 volumes from 380 eyes were acquired usi...

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Detalles Bibliográficos
Autores principales: Heisler, Morgan, Karst, Sonja, Lo, Julian, Mammo, Zaid, Yu, Timothy, Warner, Simon, Maberley, David, Beg, Mirza Faisal, Navajas, Eduardo V., Sarunic, Marinko V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2020
Materias:
Special Issue
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396168/
https://www.ncbi.nlm.nih.gov/pubmed/32818081
http://dx.doi.org/10.1167/tvst.9.2.20

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396168/
https://www.ncbi.nlm.nih.gov/pubmed/32818081
http://dx.doi.org/10.1167/tvst.9.2.20

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