Diabetic retinal diseases detection in fundus images using intelligent models

Abstract

The invention of digital cameras and various image capturing modalities has pave path for the researchers to develop automated algorithms in detection of diseases particularly in healthcare industry which helps the practitioner in screening prediction and diagnosis of human disease at an earlier stage With this technological invention and the digital imaging techniques developed particular in retinal imaging the color fundus image of human retina are widely used in the diagnosis and treatment of the eye related diseases like Diabetic Retinopathy DR Age related Macular Degeneration AMD Glaucoma and Choroidal Neovascularization CNV The effectiveness of the diagnosis and treatment mainly relies on the early detection via screening consistent However the raise in the populace and scarce in the ophthalmologist motivates the researcher to build up an automated screening and detection of retinal diseases get rid of the human error subjectivity to the inspection of human expert More number of research scholars working in this research area is exploring to make the system more effective by increasing the effectiveness of the system However it is understood from the literature study carried out that there is still space to develop the machine learning based algorithms and classifiers towards better diagnosis of retinal diseases Hence an effort has been made to develop an automated method to classify the retinal diseases with improved performance newline newline newline