This white paper describes the design goals and technical solutions of Siemens Healthineers’ next-generation DBT system, MAMMOMAT B.brilliant.
Are contrast enhanced mammography and digital breast tomosynthesis equally effective in diagnosing patients recalled from breast cancer screening?
This study one-pager includes an abstract from an external publication.
Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations.
Performance of Wide-Angle Tomosynthesis with Synthetic Mammography in Comparison to Full Field Digital Mammography.
An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload.
Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial.
Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.
Diagnostic performance of digital breast tomosynthesis for predicting response to neoadjuvant systemic therapy in breast cancer patients: A comparison with magnetic resonance imaging, ultrasound, and full-field digital mammography.
Superior Diagnostic Accuracy with Digital Breast Tomosynthesis plus Synthetic Mammograms
The following are the key findings of the clinical Premarket Approval study on the MAMMOMAT Revelation with Tomosynthesis Option.
Breast Density and Breast Cancer Screening with Digital Breast Tomosynthesis: A TOSYMA Trial Subanalysis.
Artificial Intelligence Detection of Missed Cancers at Digital Mammography That Were Detected at Digital Breast Tomosynthesis.
One view or two views for wide-angle tomosynthesis with synthetic mammography in the assessment setting?
Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis.
