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

• Published in: Translational vision science & technology Vol. 9; no. 2; p. 20
• Main Authors: Heisler, Morgan, Karst, Sonja, Lo, Julian, Mammo, Zaid, Yu, Timothy, Warner, Simon, Maberley, David, Beg, Mirza Faisal, Navajas, Eduardo V., Sarunic, Marinko V.
• Format: Journal Article
• Language: English
• Published: United States The Association for Research in Vision and Ophthalmology 13.04.2020
• Subjects: Deep Learning; Diabetes Mellitus; Diabetic Retinopathy - diagnosis; Fluorescein Angiography; Humans; Retinal Vessels; Special Issue; Tomography, Optical Coherence; deep learning; diabetic retinopathy; machine learning; optical coherence tomography; optical coherence tomography angiography

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. A total of 463 volumes from 380 eyes were acquired using the 3 × 3-mm OC...