Classification of brain MRI using SVM and KNN classifier

Abstract

The classification of the brain MRI is an important task. In this paper, the automatic approach to the classification of brain tumor into malignant Vs. benign and low grade Vs. high grade glioma is present. This method employs GLCM technique to extract the texture features from images and stored as a feature vector. The extracted features were classified using supervised SVM and KNN algorithm. The proposed system is applied on the 251 images (85 malignant and 166 benign) of clinical database and 80 images (50 low grade glioma and 30 high grade glioma) of brats 2012 training database. The accuracy of the proposed system is 96% and 86% for SVM and KNN respectively for clinical database and 85% and 72.50% for SVM and KNN respectively for Brats database.