Although computer-aided diagnosis (CAD) is widely used in mammography, conventional
CAD programs that use prompts to indicate potential cancers on the mammograms have not …

The relatively recent reintroduction of deep learning has been a revolutionary force in the
interpretation of diagnostic imaging studies. However, the technology used to acquire those …

Breast cancer is among the leading causes of mortality for females across the planet. It is
essential for the well-being of women to develop early detection and diagnosis techniques …

Background Digital breast tomosynthesis is an advancement of the mammographic
technique, with the potential to increase detection of lesions during breast cancer screening …

Background Digital breast tomosynthesis is an advancement of mammography, and has the
potential to overcome limitations of standard digital mammography. This study aimed to …

Objectives Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is
increasingly implemented in breast cancer screening. However, the large volume of images …

Importance An accurate and robust artificial intelligence (AI) algorithm for detecting cancer in
digital breast tomosynthesis (DBT) could significantly improve detection accuracy and …

The advent of large-scale high-performance computing has allowed the development of
machine-learning techniques in oncologic applications. Among these, there has been …

The two-dimensional nature of mammography makes estimation of the overall breast density
challenging, and estimation of the true patient-specific radiation dose impossible. Digital …

Tissue marker placement after image-guided breast biopsy has become a routine
component of clinical practice. Marker placement distinguishes multiple biopsied lesions …