Computer Aided System for Detection and Classification of Breast Cancer
S. Anita Shanthi · International Journal of Information Technology Control and Automation · 2012
Breast cancer is one of the most important causes of death among all type of cancers for grown-up and older women, mainly in developed countries, and its rate is rising. Since the cause of this disease is not yet known, early detection is the best way to decrease the breast cancer mortality. At present, early detection of breast cancer is attained by means of mammography. An intelligent computer-aided diagnosis system can be very helpful for radiologist in detecting and diagnosing cancerous cell patterns earlier and faster than typical screening programs. This paper proposes a computer aided system for automatic detection and classification of breast cancer in mammogram images. Intuitionistic Fuzzy C-Means clustering technique has been used to identify the suspicious region or the Region of Interest automatically. Then, the feature data base is designed using histogram features, Gray Level Concurrence wavelet features and wavelet energy features. Finally, the feature database is submitted to self-adaptive resource allocation network classifier for classification of mammogram image as normal, benign or malignant. The proposed system is verified with 322 mammograms from the Mammographic Image Analysis Society Database. The results show that the proposed system produces better results.