AN EXPERT DIAGNOSIS OF BRAIN HEMORRHAGE USING ARTIFICIAL NEURAL NETWORKS

The fundamental motivation behind this study is to identify the brain hemorrhage and to give accurate treatment so that a human life can be saved due to brain hemorrhage. Brain hemorrhage is a type of stroke which is caused by an artery in the brain bursting and causing bleeding in the surrounded tissues. Diagnosing brain hemorrhage, which is mainly through the examination of a CT scan, enables the accurate prediction of disease. This project investigates the diagnosing brain hemorrhage more accurately using an image segmentation of CT scan images using watershed method and feeding of the appropriate inputs extracted from the brain CT image to an artificial neural network for classification. The output generated as the type of brain hemorrhages, can be used to verify expert diagnosis and also as learning tool for trainee radiologists to minimize errors in current methods.