Multiclassification for Breast Cancer Image Using Voting Techniques

Abstract

Breast cancer is the most common malignancy disease that affects female population and the number of affected people is the second most common leading cause of cancer deaths among all cancer types in the developing countries. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage, it is the primary imaging modality for diagnosis of breast cancer, the basic idea of this paper is to participate in the efforts of enhancing the accuracy in medical image classification. Wepresented a classification method based on multi-classifier voting method that can aid the physician in a mammogram image classification. The study emphasizes five phases starting with the collection of images, pre-processing (image cropping of ROI), features extracting, classification and Development of multi-classifier followed by testing and evaluation. The experimental results show that the voting achieves an accuracy of 90.04%which is a good classification result compared to individual ones.