Abstract
Breast cancer is the most common cancer in women worldwide. According to the lately statistics in Taiwan, the mortality from breast cancer has become the fourth of cancerous diseases among women. In addition, younger women tend to have dense breasts and Asian women tend to have denser ones. Not only ultrasound is capable of detecting masses even in dense breasts, but also more convenient, safer, and forming the images in real-time tool for patient in regularly physical examination. Computer-aided diagnosis (CAD) has been used to discriminate between benign and malignant tumor for ultrasonic B-mode scans, but this method makes the classification largely dependent on the skill of the operator. Several studies have shown that the Nakagami parameter estimated from the ultrasonic backscattered signals can be used to assist conventional B-mode scanning when classifying breast tumors. Hence, we propose to combine ultrasonic B-mode scans with Nakagami parametric image for categorizing breast masses. We expect to acquire boundary feature and internal components of breast masses from B-mode scans and Nakagami parametric image. For boundary feature, irregular degree of contour in malignant tumor is higher than benign tumor. For internal components, the average Nakagami parameter of malignant tumor is lower than benign tumor. We used Fuzzy C-means (FCM) to separate malignant cluster and benign cluster by all parameters. The average Nakagami parameter and contour features provide complementary characteristics in diagnosis ultrasound breast tumor image. The best efficiency is that accuracy is 81.7 %, sensitivity is 80 %, and specificity is 83 %.