Overview
My research is at the intersection of computer vision, machine learning, and medical imaging, with a dual focus on mammography and computed tomography (CT). Together with our industry partner, we developed deep learning algorithms for breast cancer screening with 2D/3D mammography, and that product is now undergoing FDA approval with anticipated rollout to clinics worldwide. We also pioneer the creation of "digital twin" anatomical models from patient imaging data, using these models to forge new paths in CT scan analysis through virtual readers and deep learning techniques. Additionally, we're developing a computer-aided triage system for detecting diseases across multiple organs in body CT scans, leveraging hospital-scale datasets and integrating natural language processing with deep learning for comprehensive disease classification.
Current Appointments & Affiliations
Recent Publications
The Duke Lung Cancer Screening (DLCS) Dataset: A Reference Dataset of Annotated Low-Dose Screening Thoracic CT.
Journal Article Radiol Artif Intell · July 2025 Full text Link to item CiteXCAT 3.0: A comprehensive library of personalized digital twins derived from CT scans.
Journal Article Med Image Anal · July 2025 Virtual Imaging Trials (VIT) offer a cost-effective and scalable approach for evaluating medical imaging technologies. Computational phantoms, which mimic real patient anatomy and physiology, play a central role in VITs. However, the current libraries of c ... Full text Link to item CiteImproving annotation efficiency for fully labeling a breast mass segmentation dataset.
Journal Article J Med Imaging (Bellingham) · May 2025 PURPOSE: Breast cancer remains a leading cause of death for women. Screening programs are deployed to detect cancer at early stages. One current barrier identified by breast imaging researchers is a shortage of labeled image datasets. Addressing this probl ... Full text Link to item CiteRecent Grants
Dynamic imaging and tissue biomarker models to delineate indolent from aggressive breast calcifications
ResearchCo Investigator · Awarded by National Cancer Institute · 2022 - 2027Computer-Aided Triage of Body CT Scans with Deep Learning
ResearchPrincipal Investigator · Awarded by National Cancer Institute · 2023 - 2027FW-HTF-R: Interpretable Machine Learning for Human-Machine Collaboration in High Stakes Decisions in Mammography
ResearchCo-Principal Investigator · Awarded by National Science Foundation · 2022 - 2026View All Grants