Abstract
Diabetic Retinopathy (DR) is progressive dysfunction of the retinal blood vessels caused by chronic hyperglycemia which can be a complication of diabetes type 1 or diabetes type 2. Initially, DR is asymptomatic, if not treated though it can cause low vision and blindness. Diabetic retinopathy is responsible for 1.8 million of the 37 million cases of blindness throughout the world. So the early detection of Diabetic retinopathy through proper screening is essential.
 The paper presents a Diabetic Retinopathy Screening System which can be used as a primary diagnosis tool by ophthalmologists in the screening process to detect symptoms of Diabetic Retinopathy. The system uses the anatomical structures such as blood vessels, exudates and microaneurysms in retinal images. The retinal images are segmented and classified as normal or DR affected images by extracting features from segmented images and the Gray Level Co-occurrence Matrix (GLCM). The classifier used is Support Vector Machine (SVM) which gives a better accuracy.
 The system is implemented and tested in MATLAB and LabView for the standard database and need to be optimized for real time screening of images. LabView creates distributable .EXE files and .DLL files which can be downloaded into the FPGA/DSP processor. Hardware implementation on LabView FPGA presents a small learning curve which drastically reduces development time and eliminates the need for custom hardware design.
Highlights
The main aim of this work is to develop reliable and accurate image processing and pattern recognition methods for automatic fundus image analysis to aid ophthalmologist’s diagnosis and to be used as an automatic tool for the screening of diabetic retinopathy
Diabetic Retinopathy (DR) is progressive dysfunction of the retinal blood vessels caused by chronic hyperglycemia which can be a complication of diabetes type 1 or diabetes type 2
Diabetic Retinopathy system consists of three modules, Segmentation, feature extraction and classification is developed and tested using simulation tools Matlab and LabView
Summary
The main aim of this work is to develop reliable and accurate image processing and pattern recognition methods for automatic fundus image analysis to aid ophthalmologist’s diagnosis and to be used as an automatic tool for the screening of diabetic retinopathy. Diabetic retinopathy is a complication of diabetes to the retina It is a very asymptomatic disease in the early stages and it could lead to permanent vision loss if untreated for long time [8]. The problem here is the patients may not know about it until it reaches advanced stages Once it reaches advanced stages vision loss becomes inevitable. Diabetic retinopathy occurs because of microangiopathy which in turn affects the retinal pre-capillary arterioles, capillaries and venules. It is caused by microvascular leakages from the breakdown of the internal blood-retinal barrier and microvascular occlusion. The presence of diabetic retinopathy can be detected by examining the retina form its characteristic features [9]
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