Breast Cancer Segmentation in Digital Mammograms Based on Harmony Search Optimization

One of the serious reasons of death among women is breast cancer. Early diagnosis can help to women’s quality of life. In this context, mammography images have a most significant effectiveness. In fact, they are known as the main test used for screening and early diagnosis. Recently, computer aided mass detection techniques was an active field of research and some of these studies showed a promising future. In this paper, a new threshold algorithm based on the harmony search algorithm (HSA) is introduced. HSA is a new meta-heuristic approach which is inspired from musicians developing new harmonies while playing. The proposed method employs random samples as candidate solutions from the search space inside the image histogram with considering to the objective function that is utilized by the Kapur’s method. This objective values are achieved until an optimal solution is found. Experimental results show the high accuracy of the proposed approach for the breast cancer segmentation.