Surgeon Supervised Autonomous Surgical System for Oral and Maxillofacial Surgery

This is the authors' abstract. We don't add key points for this paper.

Oral and maxillofacial surgery (OMS) imposes an increasing workload on even the most experienced surgeons due to long operation time, high skill requirements, limited observation field, constrained workspace, and fast-growing patient population. Robot-assisted OMS is particularly challenging, requiring technological advancements to replicate complex surgical workflows executed by human surgeons and novel working concepts to properly address human-machine relationships. We introduced a Surgeon Supervised Autonomous Surgical System (SSASS) aiming to solve emerging bottlenecks in OMS. SSASS custom develops a deep-learning-assisted virtual planning module, a teeth-based monocular camera navigation module, and a six-degree-of-freedom compact robot module to function as surgeons’ auxiliary brain, eye, and hand, respectively. These three modules are further seamlessly integrated to autonomously complete most labor-intensive procedures, while prioritizing surgeons to supervise and be responsible for the overall procedure. Le Fort I experiments on five human head models demonstrated that the surgical results of SSASS closely matched the preoperative plan, with high drilling accuracy and acceptable cutting accuracy under a fundamentally new and significantly simplified surgical workflow. Compared to its existing OMS counterparts, SSASS integrates the latest technologies such as deep learning, medical 3D printing, markerless navigation, virtual reality, and collaborative robotics, providing a comprehensive surgical solution for encompassing the entire OMS loop.