| Fiscal year |
Resident |
Foundation |
Title |
| 2025 |
Sanna Herwald |
RSNA |
Prediction of Clinical Abscess Drainage Outcomes and the Efficacy of Potential Viscosity-Modifying Biochemical Treatments by Measuring Quantitative Abscess Fluid Viscosity |
| 2025 |
Davis Vigneault |
RSNA |
Developing a Fully Automated Pipeline for High-Fidelity Modelling, Measurement, and Longitudinal Comparison of Abdominal Aortic Aneurysms |
| 2025 |
Wenhui Zhou |
RSNA |
Deep Learning-Based Preoperative Tumor Margin Assessment for Personalized Surgery in Lobular Breast Cancer |
| 2024 |
Veit Sandfort |
RSNA |
Dynamic CT Evaluation of Proximal Aortic Distensibility in Stanford Type B Aortic Dissection |
| 2023 |
Wenhui Zhou |
RSNA |
Prediction of Occult Invasive Breast Cancer in Women with Ductal Carcinoma In Situ Using Multitask Deep Learning |
| 2022 |
Sanna Herwald |
SIR |
Quantitative Viscosity of Abscess Fluid: Clinical Predictors and Novel Biochemical Treatments |
| 2022 |
Ophir Vermesh |
RSNA |
Engineering Genetically-Encoded Synthetic Reporters for Dual Breath- and Imaging-Based Early Cancer Detection |
| 2022 |
Veit Sandfort |
RSNA |
Minimizing Human Labeling Effort in Cardiovascular Deep Learning Segmentation To Enable Comprehensive Risk Assessment in Type B Aortic Dissection |
| 2020 |
Eric Keller |
SIR |
Making Informed Consent an Informed Choice: Addressing Disparities in Informed Consent in Interventional Radiology |
| 2019 |
Justin R Tse |
RSNA |
CT Angiography for Acute Gastrointestinal Bleeding: Quantitative Imaging Biomarkers to Predict Clinical Outcomes |
| 2019 |
Justin R Tse |
ACR |
Expanding Global Health Radiology in Tanzania |
| 2019 |
Andrew Wentland |
RSNA |
An Artificial Intelligence Approach to Improve the Differentiation of Surgical from Non-surgical Cystic Renal Lesions |
| 2019 |
Dylan Wolman |
RSNA |
Prospective Utilization of Dual-energy CT for the Detection and Aging of Vertebral Compression Fractures in Trauma |
| 2018 |
Lewis Hahn |
RSNA |
Segmentation and Quantitative Assessment of Prognostic Features in Type B Aortic Dissection Using Machine Learning |