5 papers
External Validation of Deep Learning Models for BI-RADS Breast Density Prediction from Ultrasound Images
Yuxuan Chen, Arianna Bunnell, Yanqi Xu +4
We externally validated three deep learning models (DenseNet121, ViT-B/32, and ResNet50) for predicting mammographic breast density from breast ultrasound exams on an independent c…
Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging
Arianna Bunnell, Devon Cataldi, Yannik Glaser +6
Total-body dual X-ray absorptiometry (TBDXA) imaging is a relatively low-cost whole-body imaging modality, widely used for body composition assessment. We develop and validate a de…
Artificial Intelligence-Informed Handheld Breast Ultrasound for Screening: A Systematic Review of Diagnostic Test Accuracy
Arianna Bunnell, Dustin Valdez, Fredrik Strand +3
Background. Breast cancer screening programs using mammography have led to significant mortality reduction in high-income countries. However, many low- and middle-income countries…
Deep Learning Predicts Mammographic Breast Density in Clinical Breast Ultrasound Images
Arianna Bunnell, Dustin Valdez, Thomas K. Wolfgruber +8
Background: Breast density, as derived from mammographic images and defined by the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS), is one of the…
BUSClean: Open-source software for breast ultrasound image pre-processing and knowledge extraction for medical AI
Arianna Bunnell, Kailee Hung, John A. Shepherd +1
Development of artificial intelligence (AI) for medical imaging demands curation and cleaning of large-scale clinical datasets comprising hundreds of thousands of images. Some moda…