Diagnosis of ICH and SDH Brain Hemorrhage Using Artificial Neural Networks

Abstract

Medical Image analysis and processing has great significance in the field of medicine, especially in Non-invasive treatment and clinical study. Medical Image Processing has emerged as one of the most important tools to identify as well as diagnose various disorders. Diagnosing brain hemorrhage, which is a condition caused by a brain artery busting and causing bleeding in the surrounded tissues is currently done by medical experts using a CT scan. This paper investigates the possibility of diagnosing brain hemorrhage using an image segmentation of CT scan images using segmentation algorithm and feeding of the appropriate inputs extracted from the brain CT image to an artificial neural network for classification. Aim of this paper is to design, develop and evaluate an easy to use, intelligent and accurate system which enables users like radiologists or medical students as well as doctors to feed brain CT images to diagnose whether there is a hemorrhage and specify the type of hemorrhage using Fuzzy C means along with neural network for hemorrhage classification.