78 citations · 140 across the 29 of their papers we have counts for
10 papers · 1 filter
DualVision ArthroNav: Investigating Opportunities to Enhance Localization and Reconstruction in Image-based Arthroscopy Navigation via External Cameras
Hongchao Shu, Lalithkumar Seenivasan, Mingxu Liu +6
Arthroscopic procedures can greatly benefit from navigation systems that enhance spatial awareness, depth perception, and field of view. However, existing optical tracking solution…
TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research
Han Zhang, Yiqing Shen, Roger D. Soberanis-Mukul +11
Developing embodied AI for intelligent surgical systems requires safe, controllable environments for continual learning and evaluation. However, safety regulations and operational…
Investigating Robot Control Policy Learning for Autonomous X-ray-guided Spine Procedures
Florence Klitzner, Blanca Inigo, Benjamin D. Killeen +4
Imitation learning-based robot control policies are enjoying renewed interest in video-based robotics. However, it remains unclear whether this approach applies to X-ray-guided pro…
Constrained Natural Language Action Planning for Resilient Embodied Systems
Grayson Byrd, Corban Rivera, Bethany Kemp +5
Replicating human-level intelligence in the execution of embodied tasks remains challenging due to the unconstrained nature of real-world environments. Novel use of large language…
Egosurg: Arbitrary view synthesis for egocentric replay of operating room workflows from ambient cameras
Han Zhang, Lalithkumar Seenivasan, Jose L. Porras +10
Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric perspectives that shape clinical decisions undocumented. Ambien…
Explainable AI for Automated User-specific Feedback in Surgical Skill Acquisition
Catalina Gomez, Lalithkumar Seenivasan, Xinrui Zou +9
Traditional surgical skill acquisition relies heavily on expert feedback, yet direct access is limited by faculty availability and variability in subjective assessments. While trai…
Beyond Rigid AI: Towards Natural Human-Machine Symbiosis for Interoperative Surgical Assistance
Lalithkumar Seenivasan, Jiru Xu, Roger D. Soberanis Mukul +6
Emerging surgical data science and robotics solutions, especially those designed to provide assistance in situ, require natural human-machine interfaces to fully unlock their poten…
Position: Foundation Models Need Digital Twin Representations
Yiqing Shen, Hao Ding, Lalithkumar Seenivasan +2
Current foundation models (FMs) rely on token representations that directly fragment continuous real-world multimodal data into discrete tokens. They limit FMs to learning real-wor…
Privacy-Preserving Operating Room Workflow Analysis using Digital Twins
Alejandra Perez, Han Zhang, Yu-Chun Ku +7
The operating room (OR) is a complex environment where optimizing workflows is critical to reduce costs and improve patient outcomes. While computer vision approaches for automatic…
Online Reasoning Video Segmentation with Just-in-Time Digital Twins
Yiqing Shen, Bohan Liu, Chenjia Li +2
Reasoning segmentation (RS) aims to identify and segment objects of interest based on implicit text queries. As such, RS is a catalyst for embodied AI agents, enabling them to inte…