Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Fuzzy Image Processing

Sami Suhaila Rahim, Vasile Palade, Chrisina Jayne, Andreas Holzinger, James Shuttleworth

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in Buch/Bericht


Diabetic retinopathy is a damage of the retina and it is one of the serious consequences of the diabetes. Early detection of diabetic retinopathy is extremely important in order to prevent premature visual loss and blindness. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images using fuzzy image processing. The detection of maculopathy is essential as it will eventually cause loss of vision if the affected macula is not timely treated. The developed system consists of image acquisition, image preprocessing with a combination of fuzzy techniques, feature extraction, and image classification by using several machine learning techniques. The fuzzy-based image processing decision support system will assist in the diabetic retinopathy screening and reduce the burden borne by the screening team.
TitelBrain Informatics and Health, Lecture Notes in Artificial Intelligence LNAI
Redakteure/-innenYike Guo, Karl Friston, Aldo A. Faisal, Sean Hill, Hanchuan Peng
ErscheinungsortCham, Heidelberg, New York, Dordrecht, London
Herausgeber (Verlag)Springer International
ISBN (elektronisch)978-3-319-23344-4
ISBN (Print)978-3-319-23343-7
PublikationsstatusVeröffentlicht - 2015
VeranstaltungInteractive Machine Learning with the “human-in-the-loop”: 8th international special session of the HCI-KDD expert group - Imperial College London, London, Großbritannien / Vereinigtes Königreich
Dauer: 1 Sep 20151 Sep 2015


NameLecture Notes in Artificial Intelligence
Herausgeber (Verlag)Springer


KonferenzInteractive Machine Learning with the “human-in-the-loop”
LandGroßbritannien / Vereinigtes Königreich

ASJC Scopus subject areas

  • Artificial intelligence

Fields of Expertise

  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)
  • Experimental


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