A Novel Approach for Diagnosing Diabetic Retinopathy in Fundus Images

Abstract

Abstract:In recent years the medical profession has seen an ever increasing demand for diagnosis and a permanent cure for illnesses caused by climatic-changes, unwholesome food and environmental pollution. Also the appearances of hitherto unknown viral diseases have caused eye diseases, which have prompted surgeons to monitor the health of the eyes. Potential new therapies that may help in preserving sight in the growing population of diabetic patients into the 21st Century. Early detection of diseases affecting the eyes reduces the risk of permanent damage. Some of the serious conditions which warrant early diagnosis are: Glaucoma, floaters, macula degradation and diabetic retinopathy. In the early stages, a choice of treatment options exist, which dwindles as the disease spreads. A visual inspection of the optic disc, macula and the blood vessels of the eye requires to be done routinely. Diabetic patients run the risk of damage to retinal vessels, which are referred to as diabetic retinopathy. This may further be classified as: Non-proliferative diabetic retinopathy and proliferative diabetic retinopathy. In scientific literatures, feature extraction method has been reported for diagnosis and classification. In this study a systematic Decide, Detect, Determine and Do approach for analyzing diabetic retinopathy images has been taken up. The proposed approach gives a clearer picture of the abnormality, its type (NPDR or PDR), its status (viz., mild, moderate or severe) and finally the appropriate treatment.

Unravelling Diabetic Retinopathy Through Image Processing, Neural Networks and Fuzzy Logic – A Review

“…This paper suggested that the BV segmentation and BV tortuosity measurement would be used to know the retinal diseases severity. Dhiravidachelvi and Rajamani in 2015 have proposed [9] approach to detect the DR, types and its severity and the appropriate treatment. Pre-processing was done to remove salt and pepper noise, and the image was enhanced pixel level.…”