Automatic classification of mammographic masses by ROI cross sectional intensity profile analysis

Breast cancer represents the leading cause of fatality among cancers for women and there is still no known way of preventing this pathology. Computer aided analysis systems could be very helpful to improve both the sensitivity and the specificity. In this paper, a computer aided diagnosis system for malignant/benign masses classification of ROI in mammograms based on wavelet transform decomposition and artificial neural network (ANN) classifier is shown. The main novelty of the system is to consider only small 1D signals crossing the abnormal region, allowing to drastically reduce the amount of data to be processed. An experimental analysis performed on a set of images from DDSM database has shown the effectiveness of the proposed method.