Nowadays segmentation of retina plays a major role in diagnosis of several diseases related to blood vessels like Glaucoma detection, Diabetics, Stroke prediction, Cardio Vascular Disease diagnosis, Myocardial Ischemia and other disease related to retina. Retinal fundus images are widely used in medical field for these diagnoses. Several blood vessels are found in the retina mainly arteries and veins. These blood vessels may be bifurcated, cross each other, may break in between. Manual segmentation and analysis of this image is tedious and time consuming. False detection of disease is also possible. Several researcher undergone research to automatically segment, classify and detect the disease perfectly with least amount of time. This paper deals with all ideas posted by each researcher on automatic segmentation and analysis of retinal fundus image for automatic prediction and detection of disease.
Key words: Retinal Vessel Segmentation, Graph cut algorithm, Neural Network, Supervised algorithm.
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