Color Fundus Image of Convolutional Neural Networks for Diabetic Retinopathy Macular Edema

Abstract

DME (diabetic macular edema) is a release of excess fluid in the macula region of the retina caused by diabetes.. Diabetic retinopathy is developed eventually leading to DME. Diabetic retinopathy damages retina’s blood vessel that results in vision impartment. Two-stage methodology has been proposed  DME severity can be detected and classified using colour fundus images.  By supervised learning approach, DME is detected use standard fundus photos We can obtain the normal from DME images by capturing global characteristics and discriminating using an extraction technique. By measuring the symmetry, the rotational asymmetry metric is used to determine the magnitude of disease in the macular region. Color fundus image To determine the magnitude of Diabetes Macular Edema, this test is used. 'The specification of disease is easily identified due to this color change in the color fundus image’. With several datasets available publicly, the performance of the proposed idea evaluated. The detection performance  has The diameter of an optic a sensitivity of 100 percent and a specificity of between 74 and 90 percent With a sensitivity of 100 percent and a specificity of 97 percent, cases that need immediate referral are identified. The mild case has an accuracy of 81 percent, while the extreme case has an accuracy of 100 percent case.