Convolutional network to detect exudates in eye fundus images of diabetic subjects

Oscar Perdomo; John Arevalo; Fabio A. González

doi:10.1117/12.2256939

26 January 2017 Convolutional network to detect exudates in eye fundus images of diabetic subjects

Oscar Perdomo, John Arevalo, Fabio A. González

Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 101600T (2017) https://doi.org/10.1117/12.2256939
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina

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.

Citation Download Citation

Oscar Perdomo, John Arevalo, and Fabio A. González "Convolutional network to detect exudates in eye fundus images of diabetic subjects", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101600T (26 January 2017); https://doi.org/10.1117/12.2256939

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