Detection and Classification of Tumor from Mri Brain Images Using Kernal Support Vector Machine

Abstract

Automated and accurate classi?cation of MR brain images is extremely important for medical analysis and interpretation. In this proposed work, we presented a novel method to classify a given MR brain image as normal or abnormal. The proposed method ?rst employed wavelet transform to extract features from images, followed by applying principle component analysis (PCA) to reduce the dimensions of features. The reduced features were submitted to a kernel support vector machine (KSVM). The strategy of K-fold strati?ed cross validation was used to enhance generalization of KSVM.