Brain Tumor Detection On MR Images Using Improved Support Vector Machine

The brain may be the most important organ in the human body. Memory, vision, hearing, and other senses are all under its control, as are personality traits and the ability to judge one's own strengths and weaknesses. There are many different types of tumors, some of which can lead to cancerous growths in the brain. Tumors are most commonly caused by the stalled growth of brain cells. With the aid of automatic tumor detection algorithms using Magnetic Resonance Imaging, the most deadly brain tumor can be diagnosed quickly and accurately. Radiation imaging provides detailed information on human tissue, which aids in tumor diagnosis. The clinical device's ability to determine a tumor's location relies heavily on accurate segmentation of the Magnetic Resonance Image picture. An Magnetic Resonance Imaging scan is used to examine the patient's medical status. The goal of this work is to devise the best method for detecting tumors on brain Magnetic Resonance Imaging scans and, if that proves to be the case, to determine whether the neoplasm is benign or malignant. Once these systems are applied to Magnetic Resonance images, it takes no time at all to make a neoplasm prediction, and the subsequent accuracy makes treating patients much easier. The radiologist can make quick decisions with the help of these predictions. K-means clustering method is then used to divide the brain into distinct tissues.. This method shows promise in the classification of a variety of disorders using a certain style of Magnetic Resonance images.