Abstract:
Breast cancer is the disease that most common malignancy affects female. It has been considered as a second most common leading cause of cancer death among other type of cancer, specifically in developing countries.Most of the previous researches in mammogram images achieved low classification accuracy that because of either inaccurate features or improper classifier methods.The aim of this research is to enhance the classification accuracy in mammogram images using decision tree algorithm. The study methodology emphasis of six phases starting by collecting images, preprocessing (image cropping of region of interest), features extracting, feature selection, classification and end with testing and evaluating. The experimental results using mammogram image analysis society (MIAS) Dataset showed that this approach achieves accuracy of 87.47.
