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Semantic Segmentation of Eye Fundus Images Using Convolutional Neural Networks

Ričardas Toliušis, Olga Kurasova, Jolita Bernatavičienė
Published: 28 December 2020

Abstract: The article reviews the problems of eye bottom fundus analysis and semantic segmentation algorithms used to distinguish eye vessels, optical disk. Various diseases, such as glaucoma, hypertension, diabetic retinopathy, macular degeneration, etc., can be diagnosed by changes and anomalies of vesssels and optical disk. For semantic segmentation convolutional neural networks, especially U-Net architecture, are well suited. Recently a number of U-Net modifications have been developed that deliver excellent performance results.
Keywords: neural / eye / Net / Retinopathy / diabetic / Semantic segmentation / fundus / convolutional

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