A Teleophthalmology Support System Based on the Visibility of Retinal Elements Using the CNNs

A Teleophthalmology Support System Based on the Visibility of Retinal Elements Using the CNNs

This paper proposes a teleophthalmology support system in which we use algorithms of object detection and semantic segmentation, such as faster region-based CNN (FR-CNN) and SegNet, based on several CNN architectures such as: Vgg16, MobileNet, AlexNet, etc. These are used to segment and analyze the...

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Bibliographic Details
Main Authors: Gustavo Calderon-Auza, Cesar Carrillo-Gomez, Mariko Nakano, Karina Toscano-Medina, Hector Perez-Meana, Ana Gonzalez-H. Leon, Hugo Quiroz-Mercado
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Sensors
Subjects:
teleophthalmology
support system
quality assessment
deep learning
scanning laser ophthalmoscopes
convolutional neural networks
Online Access:https://www.mdpi.com/1424-8220/20/10/2838

Internet

https://www.mdpi.com/1424-8220/20/10/2838

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