Creating a Digital Twin of Spinal Surgery: A Proof of Concept
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Abstract (arXiv)
Surgery digitalization is the process of creating a virtual replica of real-world surgery, also referred to as a surgical digital twin (SDT). It has significant applications in various fields such as education and training, surgical planning, and automation of surgical tasks. In addition, SDTs are an ideal foundation for machine learning methods, enabling the automatic generation of training data. In this paper, we present a proof of concept (PoC) for surgery digitalization that is applied to an ex-vivo spinal surgery. The proposed digitalization focuses on the acquisition and modelling of the geometry and appearance of the entire surgical scene. We employ five RGB-D cameras for dynamic 3D reconstruction of the surgeon, a high-end camera for 3D reconstruction of the anatomy, an infrared stereo camera for surgical instrument tracking, and a laser scanner for 3D reconstruction of the operating room and data fusion. We justify the proposed methodology, discuss the challenges faced and further extensions of our prototype. While our PoC partially relies on manual data curation, its high quality and great potential motivate the development of automated methods for the creation of SDTs.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 25 of its 54 references that are in the map. First posted on arXiv 25 Mar 2024.
Builds on
25 of 54 references.
References · 25
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13 more
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Built on by
Citing papers per year: 2024: 2; 2025: 6; 2026: 1.
9 papers.
- 2024SplatFormer: Point Transformer for Robust 3D Gaussian Splattingcited by 15
- 2025Automatic Calibration of a Multi-Camera System with Limited Overlapping Fields of View for 3D Surgical Scene Reconstructioncited by 4
- 2024Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representationcited by 1
- 2025Acquiring Submillimeter-Accurate Multi-Task Vision Datasets for Computer-Assisted Orthopedic Surgerycited by 1
- 2025TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Researchcited by 1
- 2025RocSync: Millisecond-Accurate Temporal Synchronization for Heterogeneous Camera Systemscited by 1
- 2025Sound Source Localization for Spatial Mapping of Surgical Actions in Dynamic Scenescited by 0
- 2025Three-Dimensional Anatomical Data Generation Based on Artificial Neural Networkscited by 0
- 2026Training-free Detection and 6D Pose Estimation of Unseen Surgical Instrumentscited by 0
- 2026Training-free Detection and 6D Pose Estimation of Unseen Surgical Instruments26 Mar 2026
- 2025Three-Dimensional Anatomical Data Generation Based on Artificial Neural Networks24 Nov 2025
- 2025RocSync: Millisecond-Accurate Temporal Synchronization for Heterogeneous Camera Systems18 Nov 2025
- 2025TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research10 Nov 2025
- 2025Sound Source Localization for Spatial Mapping of Surgical Actions in Dynamic Scenes28 Oct 2025
- 2025Automatic Calibration of a Multi-Camera System with Limited Overlapping Fields of View for 3D Surgical Scene Reconstruction27 Jan 2025
- 2025Acquiring Submillimeter-Accurate Multi-Task Vision Datasets for Computer-Assisted Orthopedic Surgery26 Jan 2025
- 2024SplatFormer: Point Transformer for Robust 3D Gaussian Splatting10 Nov 2024
- 2024Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation26 Oct 2024