Automatic Detection of Diabetic Retinopathy in Retinal Images: A Study of Recent Advances

Abstract

Most of the people throughout the world are suffering with the disease called diabetes. In severe condition of diabetes, patient may lose vision. This could be prevented by using a method called Diabetic Retinopathy, because diabetes mostly affects retina of the eye.Diabetic Retinopathy could be prevented only by earlier detection. For this detection many research workout has been carried out previously in which they used methods like Convolutional Neural Network, Deep Neural Network, Adaptive thresholding, Gabor wavelet transform method. By using the above methods blood vessel classification can be done, exudates and fundus can be identifiedin the eye. These identified stages are classified as normal proliferative retinopathy, moderate proliferative retinopathy, severe proliferative retinopathy. For the analysis purpose we used data set of images are used like DRIVE AND STARE.  By comparing all the studies done previously, best method of diabetic retinopathy is detected,depending on the parameters like accuracy, sensitivity, specificity.