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


  • Alberto Jorge Rosales Silva Instituto Politécnico Nacional
  • Jesús Salvador Velázquez-González Instituto Politécnico Nacional
  • Francisco Javier Gallegos-Funes Instituto Politécnico Nacional
  • Guadalupe de Jesús Guzmán-Bárcenas Instituto Politécnico Nacional


Diabetic Retinopathy, early diagnosis, automatically identification, fundus images


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, Instituto Politécnico Nacional

Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Zacatenco

Jesús Salvador Velázquez-González, Instituto Politécnico Nacional

Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Zacatenco

Francisco Javier Gallegos-Funes, Instituto Politécnico Nacional

Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Zacatenco

Guadalupe de Jesús Guzmán-Bárcenas, Instituto Politécnico Nacional

Centro Interdisciplinario de Ciencias de la Salud Unidad Santo Tomas


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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. Retrieved from