RETINAL VASCULAR DISEASE DETECTION FROM RETINAL FUNDUS IMAGES USING MACHINE LEARNING

RETINAL VASCULAR DISEASE DETECTION FROM RETINAL FUNDUS IMAGES USING MACHINE LEARNING One of the essential senses in the human body is the eyesight. A human existence is meaningful in the world only by the vision. So any malfunction in the vision of the human eye has to be handled with highest priority. So even in the world, there are number of scientific technologies implement lot of changes in biomedical field, the technology related to vision finds its significance. The researchers proven that the vision blurriness or the vision loss not only caused by the change in human eye power but also reflects malfunction of other parts of the body. As, the blood vessels that carry blood oxygen flow through the body and especially the blood vessels that is at the back of the eye connects to the heart. So even the heart related disorder also reflects in the eye. Not only heart, other functions like liver, kidney and inflammatory disease reflect in human eye. So detection of retinal vascular disease is very essential. For this function, the fundus images from the retina are observed by fundus camera and then only the luminous green is considered to undergo processing. CLAHE is deployed to categorize pixels of similar characteristics and noise is removed by filters. By deploying machine learning, mean-C threshold method with convolution, computation is performed and non-vessel images are removed. By making accurate predictions, the eye-care specialist can make proper diagnosis and give good consultation to the patients. 1 P a g e RETINAL VASCULAR DISEASE DETECTION FROM RETINAL FUNDUS IMAGES USING MACHINE LEARNING Diagram ELIMINATE NON-VESE AGE &DISPLAYPREDICTION Fig.1 Block diagram 1|P a g e