Breast cancer is the most frequently diagnosed malignancy after lung cancer among women in the United States and Canada. It is estimated that approximately one in eight women will be diagnosed with breast cancer in her lifetime. Annual screening mammography has been recommended by the American Cancer Society for all women over the age of 40. Ultrasound imaging is an adjunct modality for breast cancer detection/diagnosis and provides reliable targeted screening of solid breast masses. Statistical studies indicate a 14To address and improve the identification and close observation of women who are at high risk of developing breast cancer the Medipattern Corporation has developed computeraided detection and diagnosis technologies. B-CAD is a software package developed and designed to assist the radiologists in the process of detection and diagnosis of breast ultrasound lesions. B-CAD processes ultrasound scans, extracts the edges of the breast lesions, classifies them and generates reports according to BI-RADS (Breast Imaging-Reporting and Data System). B-CAD offers both options to semi-automatically or automatically segment breast lesions. The segmentation and delineation of lesions in ultrasound images by computer-based techniques is a very challenging task due to the low contrast and specular nature of the sonograms. Additional challenges in an automatic mass segmentation algorithm arise from the presence of tumor-like structures such as cooper ligaments, glandular tissue or subcutaneous fat and tissue related textures. Highly innovative and customized pixel classification techniques have been developed to overcome the inherent difficulties of the lesion segmentation in ultrasound images. Among others, B-CAD algorithms are capable of dealing with ambiguities and uncertainties resulting from anatomical complexities and modality-induced obstacles. B-CAD processes breast ultrasound images and generates several lesion candidates and automatically highlights the one with highest relevance. However, the radiologist has the option of selecting another lesion candidate, edit it using available functionalities and save it. Consequently, B-CAD calculates relevant morphological features such as margin, shape, orientation, echo pattern etc. in order to facilitate BI-RADS categorization of the lesion to determine further actions such as additional imaging studies or biopsy.