3 papers
eess.IV2026
2D Versus 3D Diffusion for In Silico Training of Interventional X-ray AI Models
Sampath Rapuri, Jeremy Ko, Benjamin D. Killeen +2
The ability to synthesize realistic X-ray images has catalyzed the development of AI models for X-ray image-guided procedures, which otherwise suffer from a lack of available annot…
cs.HC2025
Human-AI Collaboration and Explainability for 2D/3D Registration Quality Assurance
Sue Min Cho, Alexander Do, Russell H. Taylor +1
Purpose: As surgery increasingly integrates advanced imaging, algorithms, and robotics to automate complex tasks, human judgment of system correctness remains a vital safeguard for…
cs.CV2025
FluoroSAM: A Language-promptable Foundation Model for Flexible X-ray Image Segmentation
Benjamin D. Killeen, Liam J. Wang, Blanca Inigo +5
Language promptable X-ray image segmentation would enable greater flexibility for human-in-the-loop workflows in diagnostic and interventional precision medicine. Prior efforts hav…