Mammography classification using wavelets

In this paper we evaluate the performance of applying a computer aided diagnosis system for the detection and classification of breast cancer in digital mammograms. The aim of this system is to detect microcalcifications and for this purpose it processes digitally the image, focusing on the enhancement based on the wavelet transform and a classification. The improvement of the stage of enhancement is based on the possibility of wavelets to analyse different resolutions and so it can enhance the information of abnormal lesions. Finally, depending on these abnormalities, a geometric or cluster classification of the mammogram is made, based on the roughness and number of microcalcifications of the image, respectively.