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 And The Extraction Of Reliable And Robust Measurement For Patients In Order To Describe The Morphological Changes In The Brain As The Recovery Progresses. Though A Lot Of Research On Medical Image Processing Has Been Done, Still There Is Opportunity For Further Research In The Area Of Brain Hemorrhage Diagnosis Due To The Low Accuracy Level In The Current Methods And Algorithms, Coding Complexity Of The Developed Approaches, Impracticability In The Real Environment, And Lack Of Other Enhancements Which May Make The System More Interactive And Useful. This Proposed Method Investigates The Possibility Of Diagnosing Brain Hemorrhage 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.
