摘要
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.
源语言 | 英语 |
---|---|
页(从-至) | 3813-3832 |
页数 | 20 |
期刊 | Multimedia Tools and Applications |
卷 | 77 |
期 | 3 |
DOI | |
出版状态 | 已出版 - 1 2月 2018 |