Detection of Brain Hemorrhage from CT Scan Images using ROF Filter and Classification

In the body system, the brain ranks among the most major organs. It regulates processes that affect things like sight, hearing, memory, intellect, likeability, and work-related problems. A form of strokes known as brain hemorrhage results from a burst arterial in the brain, which then causes bleeding in the surrounding structures. In this work, it describes a method for detecting brain hemorrhage using computed tomography (CT) scans. The type of hemorrhaging is also evaluated. The suggested technique consists of numerous phases, including image pre-treatment, filtration, and extraction of features. An ROF filter is used in this study to pre-process images of brain hemorrhage scans, and hemorrhage events are then classified. The method of SFTA, GLSZM and LBP feature extractions were applied to the head CT scan. A small number of pictures were sent to the Bagged Tree classifier after feature extraction, and the results were generally satisfactory.