Automated Identification of Diabetic Retinopathy Stages Using Digital Fundus Images

Abstract

Diabetic retinopathy (DR) is caused by damage to the small blood vessels of the retina in the posterior part of the eye of the diabetic patient. The main stages of diabetic retinopathy are non-proliferate diabetes retinopathy (NPDR) and proliferate diabetes retinopathy (PDR). The retinal fundus photographs are widely used in the diagnosis and treatment of various eye diseases in clinics. It is also one of the main resources for mass screening of diabetic retinopathy. In this work, we have proposed a computer-based approach for the detection of diabetic retinopathy stage using fundus images. Image preprocessing, morphological processing techniques and texture analysis methods are applied on the fundus images to detect the features such as area of hard exudates, area of the blood vessels and the contrast. Our protocol uses total of 140 subjects consisting of two stages of DR and normal. Our extracted features are statistically significant (p < 0.0001) with distinct mean +/- SD as shown in Table 1. These features are then used as an input to the artificial neural network (ANN) for an automatic classification. The detection results are validated by comparing it with expert ophthalmologists. We demonstrated a classification accuracy of 93%, sensitivity of 90% and specificity of 100%.

Diabetes Mechanisms, Detection and Complications Monitoring

“…5 [Nayak et al, 2008;Acharya et al, 2011a;Acharya et al 2009;Acharya et al, 2011b]. The green www.intechopen.com component of the RGB (Red, Green Blue) blood vessel image is considered for this study.…”

“…Fig. 6 shows the block diagram of the exudates extraction in digital fundus images Nayak et al, 2008;Acharya et al, 2011a;Acharya et al, 2011b]. The green component of the original image is extracted and subjected to the morphological closing operation by using octagonal shaped structuring element.…”

Geometrical Feature Extraction for Glaucoma Detection

“…The detection of glaucoma through Optical Coherence Tomography (OCT) and Heidelberg Retinal Tomography (HRT) are very costly [1, 2] compared to digital fundus images. It is easy to extract the features of the fundus images such as optic disc and cup to suspect the glaucoma [3,4,5].Glaucoma detection is classified into two categories: Primary open angle glaucoma and another is secondary glaucoma. In very early stage if it is diagnosed as glaucoma, that stage is called as primary open angle glaucoma.…”

The Assessment of Time-Domain Features for Detecting Symptoms of Diabetic Retinopathy

“…This disease affects many parts of body, more particularly affects blood vessels of a retina. Diabetic Retinopathy (DR) is resulted from the damage of tiny blood vessels inside diabetic patient's retina [1]. DR is a major cause of vision loss and blindness [2].…”