Improvements in mammographic acquisition techniques have resulted in making the early signs of breast cancer more apparent on mammograms. However, the accuracy of the overall mammographic examination depends on both the quality of the mammographic images and the ability of the radiologist to interpret those images. While mammography is the best screening method for the early detection of breast cancer, radiologists do miss lesions on mammograms. Use of output, however, from a computerized analysis of an image by a radiologist may help him/her in the detection or diagnostic tasks, and potentially improve the overall interpretation of breast images and the subsequent patient care. Computer-aided detection and diagnosis (CAD) involves the application of computer technology to the process of medical image interpretation. CAD can be defined as a diagnosis made by a radiologist, who uses the output from a computerized analysis of medical images as a "second opinion" in detecting and diagnosing lesions, with the final diagnosis being made by the radiologist. The computer output must be at a sufficient performance level, and in addition, the output must be displayed in a user-friendly format for effective and efficient use by the radiologist. This chapter reviews CAD in breast cancer detection and diagnosis, including examples of image analyses, multi-modality approaches (i.e., special-view diagnostic mammography, ultrasound, and MRI), and means of communicating the computer output to the human.