2 citations · 7 across the 17 of their papers we have counts for
18 papers
Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos
Chenyan Jing, Hao Ding, Lalithkumar Seenivasan +2
Vision foundation models such as SAM 3 can provide transferable object-level structure across diverse surgical video conditions, but segmentation outputs do not explicitly encode t…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
AffordTissue: Dense Affordance Prediction for Tool-Action Specific Tissue Interaction
Aiza Maksutova, Lalithkumar Seenivasan, Hao Ding +5
Surgical action automation has progressed rapidly toward achieving surgeon-like dexterous control, driven primarily by advances in learning from demonstration and vision-language-a…
SAW: Toward a Surgical Action World Model via Controllable and Scalable Video Generation
Sampath Rapuri, Lalithkumar Seenivasan, Dominik Schneider +9
A surgical world model capable of generating realistic surgical action videos with precise control over tool-tissue interactions can address fundamental challenges in surgical AI a…
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…
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…
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…
MoSFormer: Augmenting Temporal Context with Memory of Surgery for Surgical Phase Recognition
Hao Ding, Xu Lian, Mathias Unberath
Surgical phase recognition from video enables various downstream applications. Transformer-based sliding window approaches have set the state-of-the-art by capturing rich spatial-t…
Neural Finite-State Machines for Surgical Phase Recognition
Hao Ding, Zhongpai Gao, Benjamin Planche +7
Surgical phase recognition (SPR) is crucial for applications in workflow optimization, performance evaluation, and real-time intervention guidance. However, current deep learning m…
ConceptAgent: LLM-Driven Precondition Grounding and Tree Search for Robust Task Planning and Execution
Corban Rivera, Grayson Byrd, William Paul +12
Robotic planning and execution in open-world environments is a complex problem due to the vast state spaces and high variability of task embodiment. Recent advances in perception a…
StraightTrack: Towards Mixed Reality Navigation System for Percutaneous K-wire Insertion
Han Zhang, Benjamin D. Killeen, Yu-Chun Ku +9
In percutaneous pelvic trauma surgery, accurate placement of Kirschner wires (K-wires) is crucial to ensure effective fracture fixation and avoid complications due to breaching the…
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation
Hao Ding, Yuqian Zhang, Wenzheng Cheng +7
Surgical phase recognition (SPR) is an integral component of surgical data science, enabling high-level surgical analysis. End-to-end trained neural networks that predict surgical…
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance
Hongchao Shu, Mingxu Liu, Lalithkumar Seenivasan +5
Arthroscopy is a minimally invasive surgical procedure used to diagnose and treat joint problems. The clinical workflow of arthroscopy typically involves inserting an arthroscope i…
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…
Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation
Yiqing Shen, Hao Ding, Xinyuan Shao +1
Fully supervised deep learning (DL) models for surgical video segmentation have been shown to struggle with non-adversarial, real-world corruptions of image quality including smoke…
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…