Review On: An Efficient Automated System for Detection of Vision loss caused due to Diabetic Retinopathy
Keywords:
Diabetic retinopathy(DR), Macula Ischemia(MI),Vitreous haemorrhage(VH),Support vector machine(SVM),Proliferative diabetic retinopathy(PDR), Non-proliferative diabetic retinopathy(NPDR), SUSAN (Smallest Unvalued Segment Assimilating Nucleus)Abstract
Diabetes is a worldwide disease which is one of the main reason for blindness in the older age of any human community world-wide. Advanced level of diabetes leads to retinal problems called as diabetic retinopathy. Early detection of this disease is important. During pregnancy, diabetic retinopathy may also be problem for women with diabetes. This paper deals with detecting and classifying three diseases of diabetic retinopathy that are macula Ischemia, neovascularisation and vitreous haemorrhage using image processing methods. This paper mainly deals with automating detection of above three diseases in eye fundus images using digital image analysis methods which has huge potential benefits, allowing the examination of a large number of images in less time, with lower cost and reduced subjectivity than current observer-based techniques. Another advantage is the possibility to perform automated screening for pathological conditions, such as diabetic retinopathy, in order to reduce the workload required of trained manual graders.This method also uses support vector machine(svm) which is a supervised learning algorithm for both classification or regression challenges.
