A Neurofuzzy Network for Supporting Detection of Diabetic Symptoms
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.
KeywordsDiabetic Retinopathy Retinal Image Fundus Image Fuzzy Parameter Diabetic Symptom
- 4.Kavitha D, Shenbaga DS (2005) Automatic detection of optic disc and exudates in retinal images. IEEE International conference on intelligent sensing and information processing (ICISIP), pp 501–506Google Scholar
- 6.Carnimeo L, Giaquinto A (2007) A fuzzy architecture for detecting suspect diabetic symptoms in retinal images. In: 3rd WSEAS International conference on cellular and molecular biology, biophysics and bioengineering (BIO’07), pp 42–45Google Scholar