Purpose To evaluate the use of artificial intelligence (AI) to shorten digital breast
tomosynthesis (DBT) reading time while maintaining or improving accuracy. Materials and …

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

Background The high volume of data in digital breast tomosynthesis (DBT) and the lack of
agreement on how to best implement it in screening programs makes its use challenging …

Background Digital breast tomosynthesis (DBT) has higher diagnostic accuracy than digital
mammography, but interpretation time is substantially longer. Artificial intelligence (AI) could …

OBJECTIVE. Digital breast tomosynthesis (DBT) is more accurate than full-field digital
mammography alone but requires a longer reading time. A radiologist reader study …

Background Use of artificial intelligence (AI) as a stand-alone reader for digital
mammography (DM) or digital breast tomosynthesis (DBT) breast screening could ease …

Importance Breast cancer screening is among the most common radiological tasks, with
more than 39 million examinations performed each year. While it has been among the most …

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 …

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 …