Classifying Brain Anomalies Using PCA And SVM

In this research paper an automated intelligent classification system is proposed which caters the need for classification of image slices after identifying abnormal MRI volume, for anomalies identification. Features are extracted by the use of Principal component Analysis(PCA).SVM classifier is to group items that have similar feature values into two categories as normal or abnormal.RBF kernel function is to classify non-linear datas. Experimental results shows that the proposed system have high classification accuracy of 98% and outperformed all other classifiers tested. Software used is MATLAB R2012.