A review of advances in image-guided orthopedic surgery

Xingqi Fan; Qiyang Zhu; Puxun Tu; Leo Joskowicz; Xiaojun Chen

doi:10.1088/1361-6560/acaae9

A review of advances in image-guided orthopedic surgery

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

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Contribution to journal › Review article › peer-review

3 Scopus citations

Abstract

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 language	American English
Article number	02TR01
Journal	Physics in Medicine and Biology
Volume	68
Issue number	2
DOIs	https://doi.org/10.1088/1361-6560/acaae9
State	Published - 21 Jan 2023

Bibliographical note

Funding 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).

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

Keywords

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

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10.1088/1361-6560/acaae9

Cite this

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title = "A review of advances in image-guided orthopedic surgery",

abstract = "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.",

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note = "Funding 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). Publisher Copyright: {\textcopyright} 2023 Institute of Physics and Engineering in Medicine.",

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N2 - 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.

AB - 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.

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A review of advances in image-guided orthopedic surgery

Abstract

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Keywords

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