Digital Image Processing

S. Saravanakuamar ¹, R. Karthiga ², K. Sangeetha ³

Affiliations
1 Department of ECE, Adithya Institute of Technology, Coimbatore, IN
2 Department of ECE, KPR Institute of Engineering and Technology, Coimbatore, IN
3 Department of ECE, Surya Engineering College, Erode, IN

Abstract

Image processing and analysis to diagnose retinal disease such as diabetic retinopathy (DR) productive computer based screening of large, populations at low cost require robust, automated image analysis. The diabetic patients have many disorders in their eyes. This research relies on the problem of detecting those abnormalities in the eye of a diabetic patient for the earlier detection of DR. Here a methodology is presented for the automatic detection of the blood vessels and abnormalities in the eye of diabetic patients using digital image processing algorithm (DIP).DIP allows the use of much more complex algorithm for image processing and hence offers more sophisticated performance of simple task. Half of all Americans diagnosed with diabetes develop diabetic retinopathy. People with Type I (juvenile onset) and Type II (adult onset) diabetes are at risk. This condition usually doesn't develop, however, until around 10 years after the onset of diabetes. Diabetic retinopathy may also occur in pregnant women with diabetes. Most diabetic individuals approximately 90% will eventually develop some degree of retinopathy. The chances of developing diabetic retinopathy increase the longer a person has had diabetes and the more severe the case. Diabetic retinopathy (DR) can be defined as damage to microvascular system in the retina due to prolonged hyperglycaemia. The prevalence of DR in the Chennai Urban Rural Epidemiology (CURES) Eye Study in south India was 17.6 per cent, significantly lower than age-matched western counterparts. However, due to the large number of diabetic subjects, DR is likely to pose a public health burden in India. CURES Eye study showed that the major systemic risk factors for onset and progression of DR are duration of diabetes, degree of glycaemic control and hyperlipidaemia. Hypertension did not play a major role in this cross-sectional analysis. The role of oxidative stress, atherosclerotic end points and genetic factors in susceptibility to DR has been studied. It was found that DR was associated with increased intima-media thickness and arterial stiffness in type2 Indian diabetic subjects suggesting that common pathogenic mechanisms might predispose to diabetic microangiopathy. Curcumin, an active ingredient of turmeric, has been shown to inhibit proliferation of retinal endothelial cells in vivo. Visual disability from DR is largely preventable if managed with timely intervention by laser. It has been clearly demonstrated that in type 2 south Indian diabetic patients with proliferative DR who underwent Pan retinal photocoagulation, 73 per cent eyes with good visual acuity (6/9) at baseline maintained the same vision at 1 yr follow up. There is evidence that DR begins to develop years before the clinical diagnosis of type 2 diabetes. Our earlier study demonstrated that DR is present in 7 per cent of newly diagnosed subjects, hence routine retinal screening for DR even at the time of diagnosis of type 2 diabetes may help in optimized laser therapy. Annual retinal examination and early detection of DR can considerably reduce the risk of visual loss in diabetic individuals.

Keywords

Diabetic Retinopathy, Indian Subjects, Prevalence, Risk Factors, Type 2 Diabetes Mellitus.

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