Background Limited data are available regarding the accuracy of artificial intelligence (AI) algorithms trained on bilateral mammograms for second breast cancer surveillance in patients with a personal history of breast cancer treated with unilateral...
The international journal of medical robotics + computer assisted surgery : MRCAS
Apr 1, 2025
BACKGROUND: At present, breast cancer has become the cancer with the highest incidence rate in the world. Breast intervention robot is an important biopsy or targeted therapy method for breast diseases.
OBJECTIVE: The performance of a commercially available artificial intelligence (AI)-based software that detects breast arterial calcifications (BACs) on mammograms is presented.
Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI) computer-aided detection (CAD) and two radiologists. The results raised concerns about the tendency...
OBJECTIVE: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for full-field digital mammography (FFDM) when applied to synthetic mammography (SM).
Background Combined mammography and MRI screening is not universally accessible for women with intermediate breast cancer risk due to limited MRI resources. Selecting women for MRI by assessing their mammogram may enable more resource-effective scree...
Purpose To evaluate the change in digital breast tomosynthesis artificial intelligence (DBT-AI) case scores over sequential screenings. Materials and Methods This retrospective review included 21 108 female patients (mean age ± SD, 58.1 years ± 11.5)...
OBJECTIVE: There are limited data on the application of artificial intelligence (AI) on nonenriched, real-world screening mammograms. This work aims to evaluate the ability of AI to detect false negative cancers not detected at the time of screening ...
Cancer prevention research (Philadelphia, Pa.)
Jan 6, 2025
Mammographic density is a strong risk factor for breast cancer and is reported clinically as part of Breast Imaging Reporting and Data System (BI-RADS) results issued by radiologists. Automated assessment of density is needed that can be used for bot...
OBJECTIVE: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T...
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