Investigation of wave atom transform by using the classification of mammograms

This paper presents an approach for breast cancer diagnosis in digital mammograms using wave atom transform. Wave atom is a recent member of the multi-resolution representation methods. Primarily, the mammogram images are decomposed on the basis of wave atoms, and then a special set of the biggest coefficients from wave atom transform is used as a feature vector. Two different classifiers, support vector machine and k-nearest neighbors, are employed to classify mammograms. The method is tested using two different sets of images provided by MIAS and DDSM database.