Automated and accurate classification of MR brain images is of importance for the analysis
and interpretation of these images and many methods have been proposed. In this paper,
we present a neural network (NN) based method to classify a given MR brain image as
normal or abnormal. This method first employs wavelet transform to extract features from
images, and then applies the technique of principle component analysis (PCA) to reduce the
dimensions of features. The reduced features are sent to a back propagation (BP) NN, with …