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A Wavelet Based Reduced Feature Set for Classification of Brain MRI Images into Normal and Abnormal

Basavaraj S. Anami, Prakash H. Unki, Balaji T. Anvekar


In this paper, an attempt has been made to classify brain Magnetic Resonance Imaging (MRI) images as normal or abnormal. The proposed technique consists of four stages, viz. wavelet feature extraction, feature reduction using PCA, feature selection and classification using Artificial Neural Network (ANN). We have obtained the features related to brain MRI images using Stationary Wavelet Transform (SWT). The features have been selected and sorted based on the performance of individual feature using feed forward back-propagation artificial neural network (BPANN) based classifier. The experiment is conducted on axial, sagittal and coronal views of the brain images. A maximum classification accuracy rate of 98.83% is achieved for axial view. The proposed technique is more effective compared with methods reported in the literature.


Classification, Brain MRI, BPANN, SWT, PCA

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