Wavelet Features Extraction for Medical Image Classification

In this paper, we present a method for classification of medical images. Wavelet features of different modalities of medical images are extracted. Then mean and standard deviation of extracted wavelet features are computed. We utilize K-Nearest Neighbor classifier to classify medical imaging modalities as X-ray, MRI and CT. Experiments are conducted on medical database containing 4,500 images. We achieve 99.96% classification accuracy which presents the efficiency of our proposed approach.