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Diabetic Retinopathy Detection Using Deep Learning

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Modelling and Implementation of Complex Systems (MISC 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 593))

Abstract

Diabetes Mellitus (DM) is one of the well known metabolic illnesses. It occurs due to an excessive high level of the body’s blood sugar. I fact, this disease affects 463 million people worldwide, and this number is projected to reach 700 million by 2045, making it a serious public health problem. Diabetic Retinopathy (DR) is the most common specific complication of DM. DR is a leading cause of blindness among working-age adults. Early identification and treatment of DR can lower the risk of vision loss greatly. Since a manual diagnosis is prone to misdiagnosis and requires more effort, the automated methods for DR detection are cost and time effective. Deep learning is becoming a popular strategy to improve solutions in a range of fields, and in particular medical image analysis and classifications. In this paper, we are interested to propose a new convolutional neural network (CNN) for color fundus images. These images are pre-processed with various filters before being fed into the training model. Experimental results, in this work, are very encouraging and they outperform results of similar works in literature.

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Acknowledgements

This work is achieved in the merged team T.I.A.S.M (Technique de l’IA pour le Soutien de la Medecine) under the agreement of the Algerian Ministry of High Education and Scientific Research and the DGRSDT (Direction Générale de la Recherche Scientifique et du Développement Technologique).

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Authors and Affiliations

  1. LINFI Laboratory, Biskra University, Biskra, Algeria

    Kaouthar Manar Fellah, Samir Tigane & Laid Kahloul

Authors
  1. Kaouthar Manar Fellah
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  2. Samir Tigane
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  3. Laid Kahloul
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Corresponding author

Correspondence to Laid Kahloul .

Editor information

Editors and Affiliations

  1. Faculty of New Information and Communication Technologies, University of Constantine2, Constantine, Algeria

    Salim Chikhi

  2. Sistemas Informáticos, Universidad de Castilla - La Mancha, Albacete, Spain

    Gregorio Diaz-Descalzo

  3. Faculty of Technology, University of Saida, Saida, Algeria

    Abdelmalek Amine

  4. Faculty of Information and Communication Technology, University of Constantine2, Constantine, Algeria

    Allaoua Chaoui

  5. Faculty of New Information and Communication Technologies, Université Constantine 2, Constantine, Algeria

    Djamel Eddine Saidouni

  6. Department of Mathematics and Computer Science, University of El Oued, El-Oued, Algeria

    Mohamed Khireddine Kholladi

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Fellah, K.M., Tigane, S., Kahloul, L. (2023). Diabetic Retinopathy Detection Using Deep Learning. In: Chikhi, S., Diaz-Descalzo, G., Amine, A., Chaoui, A., Saidouni, D.E., Kholladi, M.K. (eds) Modelling and Implementation of Complex Systems. MISC 2022. Lecture Notes in Networks and Systems, vol 593. Springer, Cham. https://doi.org/10.1007/978-3-031-18516-8_17

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  • DOI: https://doi.org/10.1007/978-3-031-18516-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18515-1

  • Online ISBN: 978-3-031-18516-8

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