Creating a Digital Twin of Spinal Surgery: A Proof of Concept
This work addresses the need for virtual replicas in surgery to enhance education, planning, and automation, though it is incremental as a proof-of-concept with manual curation.
The authors tackled the problem of creating a surgical digital twin for spinal surgery by developing a proof-of-concept system that uses multiple cameras and scanners to dynamically reconstruct the surgical scene, achieving high-quality results that motivate further automation.
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.