@inproceedings{c7941533a9a24d6e9a0b34bda9263fd4,
title = "Convolutional network to detect exudates in eye fundus images of diabetic subjects",
abstract = "Diabetic retinopathy has several clinical data sources for medical diagnosis, but the lack of tools to process the data generates a subjective and unclear diagnosis. The use of convolutional networks to analyze and extract features in eye fundus images may help with an automatic detection to support medical personnel in the grading of diabetic retinopathy. This paper presents a description of convolutional neural networks as a good methodology to detect and discriminate between exudate and healthy regions in eye fundus images.",
author = "Oscar Perdomo and John Arevalo and Gonzalez, {Fabio A.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 12th International Symposium on Medical Information Processing and Analysis, SIPAIM 2016 ; Conference date: 05-12-2016 Through 07-12-2016",
year = "2017",
doi = "10.1117/12.2256939",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Eduardo Romero and Natasha Lepore and Jorge Brieva and Ignacio Larrabide",
booktitle = "12th International Symposium on Medical Information Processing and Analysis",
address = "United States",
}
