Ultrasonography plays an essential role in breast cancer diagnosis. Current deep learning based studies train the models on either images or videos in a centralized learning manner, lacking consideration of joint benefits between two different modali...
PURPOSE: To establish a reliable machine learning model to predict malignancy in breast lesions identified by ultrasound (US) and optimize the negative predictive value to minimize unnecessary biopsies.
Identifying systemic disease with medical imaging studies may improve population health outcomes. Although the pathogenesis of peripheral arterial calcification and coronary artery calcification differ, breast arterial calcification (BAC) on mammogra...
BACKGROUND: This study aimed to develop a BI-RADS network (DL-UM) via integrating ultrasound (US) and mammography (MG) images and explore its performance in improving breast lesion diagnosis and management when collaborating with radiologists, partic...
BACKGROUND: Breast magnetic resonance imaging (MRI) protocols often include T2-weighted fat-saturated (T2w-FS) sequences, which support tissue characterization but significantly increase scan time. This study aims to evaluate whether a 2D-U-Net neura...
Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and automatic molecular subtype classification in breast cancer. Materials and Methods This retrospective multicenter study included patients with biopsy-p...
Purpose To test a commercial artificial intelligence (AI) system for breast cancer detection at the BC Cancer Breast Screening Program. Materials and Methods In this retrospective study of 136 700 female individuals (mean age, 58.8 years ± 9.4 [SD]; ...
This study develops a comprehensive framework that integrates computational fluid dynamics (CFD) and machine learning (ML) to predict milk flow behavior in lactating breasts. Utilizing CFD and other high-fidelity simulation techniques to tackle fluid...
Purpose To evaluate cancer detection and marker placement accuracy of two artificial intelligence (AI) models developed for interpretation of screening mammograms. Materials and Methods This retrospective study included data from 129 434 screening ex...
BACKGROUND: Breast reduction is a common procedure with growing rates in the United States of America, aimed at alleviating the physical and psychological burdens of macromastia. Despite high success rates, it carries a risk of complications, with in...
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