Breast Cancer Detection And Classification In High Resolution Ultrasound Images

Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment and save lives. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast. In order to eliminate the operator dependency and improve the diagnostic accuracy, computer-aided diagnosis (CAD) system is a valuable and beneficial means for breast cancer detection and classification. The performance of the CAD system is fairly evaluated. Generally, a CAD system consists of four stages: preprocessing, image segmentation, feature extraction and selection, and classification. Masses and microcalcification are both important signs of breast cancer. In this paper, they are identified and classified into benign and malignant.