A Novel Brain Tumor Classification Algorithm using SVM Classifier

Abstract

This study provides an intelligent classification method for distinguishing between abnormal and normal MRI brain images. Medical pictures like MRI, ECG, and CTscan pictures are vital tools for accurately diagnosing human disease. Whenever a lot of MRIs need to be examined, traditional approach of manual tumour analysis, which relies on visual examination by a physician and radiologist, might lead to inaccurate classification. To remove human mistakes, a proposal is made for an intelligent classification system that responds to the essentials of image classification. Brain tumours are one of the primary causes of human mortality. If a tumor is diagnosed appropriately at an early stage, the chances of survival can be improved. The human brain is studied using the MRI method. The acronym MRI stands for magnetic resonance imaging. In this study, classification strategies based on Support Vector Machines (SVM) are proposed and used to brain imaging categorization. In this research, grayscale, symmetry, and texture features are utilised to extract features from MRI images. The fundamental objective of this study is to offer a decent classification result (improved accuracy and lower error rate) to detect MRI brain tumours with help of SVM. Keywords— Brain tumor, Classification, SVM, MRI.