Monte Carlo generation of benign and malignant masses inside mammograms

Abstract

It is a fact that breast cancer is the most common cancer among women in the western world. The most reliable radiographic tool for the detection and diagnosis of breast cancer is mammography. Interpreting a mammographic image is a difficult task and prone to many errors, thus physicists-radiologists are trained very well. Many CAD (computer-aided detection) systems have been developed in order to provide assistance to radiologists by classifying any mammographic lesions as benign or malignant but their reliability is yet to be proved. The most accurate way of spotting masses on the breast, until now, is radiologist’s opinion, making their training even more crucial. In this paper a method which simulates all the possible masses and place them on a mammography randomly using Monte Carlo technique, is proposed. After a comprehensive study of many different mammographic images, the final algorithm generates masses within a mammography, which in most cases a radiologist expert could not make the difference between a real mass and a generated one. The proposed method takes into account as many as possible variables for the generation of masses. There are definitely some improvements that could be developed in the future, mostly regarding the position of masses within the breast