Abstract
Breast abnormalities are the early symptoms of breast cancers. They may also bring in psychoemotional stresses to women. In this study, we developed a new automatic program based on wavelet energy entropy (WEE) and linear regression classifier (LRC): First, we segment region of interest from mammogram images. Second, we calculate WEE from the segmented images. Third, LRC was used as the classifier. We named our method as "WEE + LRC". The experiment used 10-fold stratified cross validation that was repeated 10 times. The statistical results showed the classification result was the best when the decomposition level was 4, with a sensitivity of 92.00 +/- 3.20%, a specificity of 91.70 +/- 3.27%, and an accuracy of 91.85 +/- 2.21%. The proposed method was superior to other five state-of-the-art methods. In all, our method is effective in detecting abnormal breasts.