A CAD SYSTEM FOR THE DETECTION OF MALIGNANT TUMORS IN DIGITIZED MAMMOGRAM FILMS

The high incidence of breast cancer in women has increased significantly in the recent years. The most familiar breast tumors types are mass and microcalcification. Mammograms—breast X-ray—are considered the most reliable method in early detection of breast cancer. Computer-aided diagnosis system (CAD) can be very helpful for radiologist in detection and diagnosing abnormalities earlier and faster than traditional screening programs. We proposed in this paper a method to detect malignant tumors which is a three-step process. The first step is ROI extraction of 256 x 256 pixels size. The second step is the feature extraction, where we used a set of 99 features and we found that 83 of these feature are capable of differentiating between normal and cancerous breast tissues. The third step is the classification process. We used the techniques of the minimum distance, the k-Nearest Neighbor (k-NN) and Bayes classifiers to classify between normal and cancerous tissues. We examined the effect of changing the size of ROI extracted from the mammogram on the system by extracting ROI of size 512 x 512. Our computerized scheme was shown to have the potential to detect malignant tumors with a clinically acceptable sensitivity and low false positives.