PREDICTING BREAST CANCER TUMOR BY MEANS OF MAMMOGRAPHIC IMAGE PROCESSING

Abstract

reast cancer is a disease that accounts for a disturbingly large number of deaths in females each year. Although mammographic screening is the most effective method currently available for the early detection of breast cancer, it is far from being an infallible procedure. Mammographic reading is error prone, partly because of the complexity of the task and partly because of the variability in human performance. Computers offer high reproducibility, and when used as an adjunct by the radiologist, may improve diagnostic accuracy and thus the mammographic screening process. The goal of this research was to create using Mammogram Image Processing interface that support the complex segmentation, feature extraction, and classification algorithms.