A Study On Automatic Detection Of Macular Disorders Using Retinal Fundus Images

Abstract

newlineThe people of the most developed countries in the world are facing diseases like diabetes with an increase in age. According to the survey done by the International Diabetes Federation (IDF) in 2017 states that, as of now 425million people on the earth are experiencingdiabetes and in that India is the second biggest nation. It is one of the main causes of visual impairment of the diabetic patients in the country, if not managed and treated properly. One way to attain reduction in the percentage of visual impairment caused by diabetes is early detection and diagnosis of diabetes and its disorders. newlineMedical imaging is experiencing an intense growth in recent years due to rise in the use of digital imaging systems for medical diagnostics. In the field of ophthalmology human retinal image helps in finding many eye disorders for ophthalmologists, such as glaucoma, diabetic retinopathy and macular degeneration. These diseases can prompt visual deficiency on the off chance that they are not recognized in time with flawlessness. Consequently, the retinal image investigation has been a testing research zone that means to give methods to aid the early identification of many eye illnesses. Ordinary methods depend on manual perception which is greatly inclined to error. Thus, automatic system for detection of retinal diseases is needed. newlineIn this thesis, we have proposed a system for automatic detection and grading of diabetic maculopathy stages and detection of Age Related Macular Degeneration (AMD). The proposed system will take a color retinal image as input and detects presence of DM and ARMD. Initially, the retinal images are captured with the assistance of fundus camera and preprocessed using image processing techniques to enhance the quality of the image. newlineAutomatic analysis of retinal images requires knowledge and the properties of anatomical structures and retinal lesions. Thus, after preprocessing we need to locate anatomical components of the retina, such as the fovea, optic disc, blood vessels.