Jordan University of Science and Technology

Breast Cancer Diagnosis Using Machine Learning Based on Statistical and Texture Features Extraction

Authors:  K. Al-Darabsah and M. Al-Ayyoub

Recently, Computer-Aided Diagnosis systems (CAD) have been used more to assist the health professionals in their work. This paper introduces a CAD methodology to diagnose the breast cancer successfully by distinguishing the masses in the mammogram images into benign or malignant masses. This results will help the experts to make their decision faster without doubts, and more importantly to determine the course of treatment. In this paper, we used an iterative algorithm to obtain the mass from the mammogram image. After that a classifier algorithm will run to decide the type of the mass. This method showed good results after testing it on images taken from DDSM (Digital Database for Screening Mammography).