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A Neurofuzzy Network for Supporting Detection of Diabetic Symptoms

  • Leonarda Carnimeo
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 27)

Abstract

In this paper a neurofuzzy network able to enhance contrast of retinal images for the detection of suspect diabetic symptoms is synthesized. Required fuzzy parameters are determined by ad hoc neural networks. Contrast-enhanced images are then segmented to isolate suspect areas by an adequate thresholding, which minimizes classification errors. In output images suspect diabetic regions are isolated. Capabilities and performances of the suggested network are reported and compared to scientific results.

Keywords

Diabetic Retinopathy Retinal Image Fundus Image Fuzzy Parameter Diabetic Symptom 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Dipartimento di Elettrotecnica ed ElettronicaPolitecnico di Bari4 70125 BARI – Italy

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