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…
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…
Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound
Arianna Bunnell, Yannik Glaser, Dustin Valdez +6
Detecting and classifying lesions in breast ultrasound images is a promising application of artificial intelligence (AI) for reducing the burden of cancer in regions with limited a…
Quantitative Imaging Principles Improves Medical Image Learning
Lambert T. Leong, Michael C. Wong, Yannik Glaser +4
Fundamental differences between natural and medical images have recently favored the use of self-supervised learning (SSL) over ImageNet transfer learning for medical image applica…