MRI Brain Cancer Classification Using Support Vector Machine

This research paper proposes an intelligent classification technique to recognize normal and abnormal MRI brain image. Medical image like ECG, MRI and CT-scan images are important way to diagnose disease of human being efficiently. The manual analysis of tumor based on visual inspection by radiologist/physician is the conventional method, which may lead to wrong classification when a large number of MRIs are to be analyzed. To avoid the human error, an automated intelligent classification system is proposed which caters the need for classification of image. One of the major causes of death among people is Brain tumor. The chances of survival can be increased if the tumor is detected correctly at its early stage. Magnetic resonance imaging (MRI) technique is used for the study of the human brain. In this research work, classification techniques based on Support Vector Machines (SVM) are proposed and applied to brain image classification. In this paper feature extraction from MRI Images will be carried out by gray scale, symmetrical and texture features. The main objective of this paper is to give an excellent outcome (i.e. higher accuracy rate and lower error rate) of MRI brain cancer classification using SVM.