Breast Cancer Classification Enhancement Based on Entropy Method

Ali Salem Ali Bin Sama, Saeed Mohammed Saeed Baneamoon
2017 International Journal of Engineering and Applied Computer Science  
Breast cancer is the most common form of cancer diseases among women and the second leading cause of cancer deaths worldwide. However, due to some limitations in mammography, it is difficult to classify a suspicious mass in the breast as malignant (cancerous) or benign. This paper attempts to classify the mammographic masses with high accuracy by combining entropy method with evolutionary algorithm (EA) and fuzzy logic. EA and fuzzy logic are applied at training phase for parameters tuning,
more » ... ver, entropy method is applied at training phase and localization phase, where at training phase entropy enhances indicator of fuzziness, while at mass phase entropy enhances EA for the classification of masses in mammogram images. The proposed method is evaluated by experimenting a number of the benchmark Mini-MIAS databases and the results shows better and more effective identification.
doi:10.24032/ijeacs/0208/06 fatcat:hmohzvvuznelplhbnn7ugglgr4