8 papers
Patient-Specific Articulated Digital Twins from a Single Full-Body CT Scan
Han Zhang, Boyang Zhao, Mathias Unberath
Patient-specific anatomical models provide individualized context for surgical planning, image-guided intervention, and algorithm development. However, most CT-derived models are s…
Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA
Yiqing Shen, Han Zhang, Mathias Unberath
Surgical video question answering requires multi-step reasoning across semantic, spatial, and temporal dimensions. Existing methods architecturally compress videos into discrete to…
Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models
Hao Ding, Lalithkumar Seenivasan, Hongchao Shu +7
Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning complex action sequences. Sound plann…
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…
Humanoid Robots as First Assistants in Endoscopic Surgery
Sue Min Cho, Jan Emily Mangulabnan, Han Zhang +7
Humanoid robots have become a focal point of technological ambition, with claims of surgical capability within years in mainstream discourse. These projections are aspirational yet…
Did you just see that? Arbitrary view synthesis for egocentric replay of operating room workflows from ambient sensors
Han Zhang, Lalithkumar Seenivasan, Jose L. Porras +9
Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric visual perspectives that guide clinical decisions undocumented.…