Breast cancer is the second-most common and leading cause of cancer death among
women. It has become a major health issue in the world over the past 50 years, and its …

Artificial intelligence (AI) is already widely employed in various medical roles, and ongoing
technological advances are encouraging more widespread use of AI in imaging. This is …

Recent advances in machine learning yielded new techniques to train deep neural
networks, which resulted in highly successful applications in many pattern recognition tasks …

In this paper, we developed a deep convolutional neural network (CNN) for the classification
of malignant and benign masses in digital breast tomosynthesis (DBT) using a multi-stage …

Screening mammography is an important front-line tool for the early detection of breast
cancer, and some 39 million exams are conducted each year in the United States alone …

Computer-aided diagnosis (CAD), encompassing computer-aided detection and
quantification, is an established and rapidly growing field of research. In daily practice …

The roles of physicists in medical imaging have expanded over the years, from the study of
imaging systems (sources and detectors) and dose to the assessment of image quality and …

Three-dimensional computerized characterization of biomedical solid textures is key to large-
scale and high-throughput screening of imaging data. Such data increasingly become …

The role of breast image analysis in radiologists' interpretation tasks in cancer risk
assessment, detection, diagnosis, and treatment continues to expand. Breast image analysis …

Background The sensitivity of screening mammography for the detection of small breast
cancers is higher when the mammogram is read by two readers rather than by a single …