A review of advances in image-guided orthopedic surgery

Xingqi Fan, Qiyang Zhu, Puxun Tu, Leo Joskowicz, Xiaojun Chen*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations


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.

Original languageAmerican English
Article number02TR01
JournalPhysics in Medicine and Biology
Issue number2
StatePublished - 5 Jan 2023

Bibliographical note

Publisher Copyright:
© 2023 Institute of Physics and Engineering in Medicine.


  • image-guided orthopedic surgery
  • intra-operative navigation
  • medical image segmentation
  • pre-operative planning


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