A review of advances in image-guided orthopedic surgery.

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

Journal

Physics in medicine and biology
ISSN: 1361-6560
Titre abrégé: Phys Med Biol
Pays: England
ID NLM: 0401220

Informations de publication

Date de publication:
05 01 2023
Historique:
received: 15 06 2022
accepted: 12 12 2022
pubmed: 4 1 2023
medline: 12 1 2023
entrez: 3 1 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 36595258
doi: 10.1088/1361-6560/acaae9
doi:

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023 Institute of Physics and Engineering in Medicine.

Auteurs

Xingqi Fan (X)

Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

Qiyang Zhu (Q)

Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

Puxun Tu (P)

Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

Leo Joskowicz (L)

School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.

Xiaojun Chen (X)

Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

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Classifications MeSH