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
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.