Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in artificial intelligence (AI), deep learning (DL), augmented reality (AR) and robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and DL based medical image segmentation, 3D visualization and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with AR and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.
Bibliographical noteFunding Information:
This work was supported by grants from National Key R&D Program of China (2022YFE0197900), National Natural Science Foundation of China (81971709; M-0019;82011530141), the Foundation of Science and Technology Commission of Shanghai Municipality (20490740700), Shanghai Jiao Tong University Foundation on Medical and Technological Joint Science Research (YG2019ZDA06; YG2021ZD21; YG2021QN72; YG2022QN056), 2020 Key Research Project of Xiamen Municipal Government (3502Z20201030), and Israel-China Grant from the Israel Ministry of Innovation, Science and Technology (3-18132).
© 2023 Institute of Physics and Engineering in Medicine.
- image-guided orthopedic surgery
- intra-operative navigation
- medical image segmentation
- pre-operative planning