Abstract— Brain hemorrhage is a type of stroke, which occurs due to artery bursting in the brain, 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. The aim of this project is to help radiologist as well as medical students in diagnosis of brain hemorrhage in more refined manner by feeding CT images & identify the type of brain hemorrhage using watershed algorithm along with artificial neural network.
Keywords - Computed tomography (CT), Artificial Neural Networks (ANN), Back Propagation Network (BPN), Gray Level Co-occurrence Matrix (GLCM).
I. INTRODUCTION
This Brain hemorrhage is a type of stroke, which occurs due to artery bursting in the brain, causing bleeding in the surrounded tissues. The symptoms of brain hemorrhage are a sudden severe headache, Weakness in an arm or leg, nausea or vomiting, changes in vision, difficulty in speaking or understanding speech, difficulty in
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Sometimes deep hemorrhages can expand into the ventricles – the fluid filled spaces in the center of the brain.
Subdural hemorrhage (SDH): Subdural hemorrhage (SDH) is a collection of blood accumulating in the potential space between the dura and arachnoid mater of the meninges around the brain.
Extradural hemorrhage (EDH): An extradural hemorrhage (EDH), also known as an epidural hemorrhage, is bleeding between the inside of the skull and the outer covering of the brain (called the "dura").
Subarachnoid hemorrhage (SAH): Subarachnoid hemorrhage (SAH) is a serious, life-threatening type of stroke caused by bleeding into the space surrounding the