Tumor Detection and Classification of MRI Brain Image using Support Vector Machine (SVM)

Abstract

Brain is one of the most complex organs in the human body that works with billions of cells. A cerebral tumor occurs when there is an uncontrolled division of cells that form an abnormal group of cells around or within the brain. This cell group can affect the normal functioning of brain activity and can destroy healthy cells. Brain tumors are classified as benign or low-grade and malignant tumors or high-grade. Benign tumors are non-cancerous tumor and they do not spread to other tissues or organs. Malignant tumors are cancerous tissue and they can easily spread to other tissues or organs. Proposed system is to differentiate between normal brain and tumor brain (benign or malign). Also, the proposed system predicts brain tumor from MRI image classification system is based on extracting useful MRI features for diagnosing the medical MRI images. The benefits of using SVM is nevertheless of the image brightness or rotation of the MRI image, it also provides huge number of strong features that can be automatically prepared well to be suitable for MRI classification. Support Vector Machine (SVM) algorithm is used to predict the diseases accurately from MRI (Magnetic Resonance Imaging) scan images. SVM algorithm is the used for the purpose of classifying the image datasets and to predict the disease by itself for those matching the images to enhance a comprehensive set of quantitative measurements among several influential on various brain image databases.