Detection and classification of Non-Proliferative Diabetic Retinopathy using a Back-Propagation neural network


  • Alberto Jorge Rosales-Silva National Polytechnic Institute
  • Jesús Salvador Velázquez-González National Polytechnic Institute
  • Francisco Javier Gallegos-Funes National Polytechnic Institute
  • Guadalupe de Jesús Guzmán-Bárcenas National University of Colombia



early diagnosis, automatically identification, fundus images, diabetic Retinopathy, diabetic retinopathy


One of the most serious complications of type 2 Diabetes Mellitus (DM) is the Diabetic Retinopathy (DR). DR is a silent disease and is only recognized when the changes on the retina have progressed to a level at which treatment turns complicate, so an early diagnosis and referral to an ophthalmologist or optometrist for the management of this disease can prevent 98% of severe visual loss. The aim of this work is to automatically identify Non Diabetic Retinopathy (NDR), and Background Retinopathy using fundus images. Our results show a classification accuracy of 92%, with sensitivity and specifity of 95%.

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Author Biographies

Alberto Jorge Rosales-Silva, National Polytechnic Institute

Higher School of Mechanical and Electrical Engineering Zacatenco Unit.

Jesús Salvador Velázquez-González, National Polytechnic Institute

Higher School of Mechanical and Electrical Engineering Zacatenco Unit.

Francisco Javier Gallegos-Funes, National Polytechnic Institute

Higher School of Mechanical and Electrical Engineering Zacatenco Unit.

Guadalupe de Jesús Guzmán-Bárcenas, National University of Colombia

Interdisciplinary Center for Health Sciences Santo Tomas Unit.


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How to Cite

Rosales-Silva, A. J., Velázquez-González, J. S., Gallegos-Funes, F. J., & Guzmán-Bárcenas, G. de J. (2015). Detection and classification of Non-Proliferative Diabetic Retinopathy using a Back-Propagation neural network. Revista Facultad De Ingeniería Universidad De Antioquia, (74), 70–85.

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