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 …

Purpose To investigate how an artificial intelligence (AI) system performs at digital
mammography (DM) from a screening population with ground truth defined by digital breast …

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

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 …

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

Objective The purpose of this study is to assess the “real-world” impact of an artificial
intelligence (AI) tool designed to detect breast cancer in digital breast tomosynthesis (DBT) …

Background There is growing evidence that digital breast tomosynthesis (DBT) results in
lower recall rates and higher cancer detection rates when compared with digital …

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

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 …

Objectives Digital breast tomosynthesis (DBT) can detect more cancers than the current
standard breast screening method, digital mammography (DM); however, it can substantially …