The use of digital breast tomosynthesis (DBT) in breast cancer screening has become
widely accepted, facilitating increased cancer detection and lower recall rates compared …

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 …

“Just Accepted” papers have undergone full peer review and have been accepted for
publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout …

The ultimate goals of the application of artificial intelligence (AI) to digital breast
tomosynthesis (DBT) are the reduction of reading times, the increase of diagnostic …

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 …

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

Artificial intelligence (AI) and particularly the introduction of deep learning convolutional
neural networks brings new potential in computer-aided detection systems. In the context of …

Rationale and Objectives With the growing adoption of digital breast tomosynthesis (DBT) in
breast cancer screening, we compare the performance of deep learning computer-aided …

Digital breast tomosynthesis (DBT) has been widely adopted in breast imaging in both
screening and diagnostic settings. The benefits of DBT are well established. Compared with …

Digital Breast Tomosynthesis (DBT) provides three-dimensional images of the breast that
enable radiologists to discern whether densities are due to overlapping structures or lesions …