Virtual Reality for Synergistic Surgical Training and Data Generation
Not on the map. Why?
Abstract (arXiv)
Surgical simulators not only allow planning and training of complex procedures, but also offer the ability to generate structured data for algorithm development, which may be applied in image-guided computer assisted interventions. While there have been efforts on either developing training platforms for surgeons or data generation engines, these two features, to our knowledge, have not been offered together. We present our developments of a cost-effective and synergistic framework, named Asynchronous Multibody Framework Plus (AMBF+), which generates data for downstream algorithm development simultaneously with users practicing their surgical skills. AMBF+ offers stereoscopic display on a virtual reality (VR) device and haptic feedback for immersive surgical simulation. It can also generate diverse data such as object poses and segmentation maps. AMBF+ is designed with a flexible plugin setup which allows for unobtrusive extension for simulation of different surgical procedures. We show one use case of AMBF+ as a virtual drilling simulator for lateral skull-base surgery, where users can actively modify the patient anatomy using a virtual surgical drill. We further demonstrate how the data generated can be used for validating and training downstream computer vision algorithms
Key facts. Cited by 6 papers in the map (data through 13 Oct 2026). First posted on arXiv 15 Nov 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 2; 2023: 3; 2024: 0; 2025: 1.
6 papers.
- 2023Human-in-the-loop Embodied Intelligence with Interactive Simulation Environment for Surgical Robot Learningcited by 11
- 2023Pelphix: Surgical Phase Recognition from X-ray Images in Percutaneous Pelvic Fixationcited by 8
- 2022TAToo: Vision-based Joint Tracking of Anatomy and Tool for Skull-base Surgerycited by 3
- 2023LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AIcited by 1
- 2025TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Researchcited by 1
- 2022Twin-S: A Digital Twin for Skull-base Surgerycited by 0
- 2025TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research10 Nov 2025
- 2023Pelphix: Surgical Phase Recognition from X-ray Images in Percutaneous Pelvic Fixation18 Apr 2023
- 2023LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AI5 Feb 2023
- 2023Human-in-the-loop Embodied Intelligence with Interactive Simulation Environment for Surgical Robot Learning1 Jan 2023
- 2022TAToo: Vision-based Joint Tracking of Anatomy and Tool for Skull-base Surgery29 Dec 2022
- 2022Twin-S: A Digital Twin for Skull-base Surgery21 Nov 2022