Multiclassification For Medical Images Using Voting Method

Abstract

Breast cancer is the disease most common malignancy 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. Nowadays, there is no sure way to prevent breast cancer, because its cause is not yet fully known. But there are things you can do that might lower risk such as early detection of breast cancer can play an important role in reducing the associated morbidity and mortality rates. The basic idea of this study is to a proposed classification method based on multi classifier voting method that can aid the physician in a mammogram image classification. The study emphasis of five phases starting in collect images, preprocessing (image cropping of ROI), features extracting, classification and end with testing and evaluating. The experimental results using MIAS Dataset show that the voting method achieves accuracy of 76.47. We recommend to use more than three classifiers to achieve better performance in terms of accuracy.