Educational Overview of the Concept and Application of Computer Vision in Arthroplasty.
artificial intelligence
computer vision
data science
deep learning
total hip arthroplasty
total knee arthroplasty
Journal
The Journal of arthroplasty
ISSN: 1532-8406
Titre abrégé: J Arthroplasty
Pays: United States
ID NLM: 8703515
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
14
12
2022
revised:
10
08
2023
accepted:
11
08
2023
pmc-release:
01
10
2024
medline:
25
9
2023
pubmed:
27
8
2023
entrez:
26
8
2023
Statut:
ppublish
Résumé
Image data has grown exponentially as systems have increased their ability to collect and store it. Unfortunately, there are limits to human resources both in time and knowledge to fully interpret and manage that data. Computer Vision (CV) has grown in popularity as a discipline for better understanding visual data. Computer Vision has become a powerful tool for imaging analytics in orthopedic surgery, allowing computers to evaluate large volumes of image data with greater nuance than previously possible. Nevertheless, even with the growing number of uses in medicine, literature on the fundamentals of CV and its implementation is mainly oriented toward computer scientists rather than clinicians, rendering CV unapproachable for most orthopedic surgeons as a tool for clinical practice and research. The purpose of this article is to summarize and review the fundamental concepts of CV application for the orthopedic surgeon and musculoskeletal researcher.
Identifiants
pubmed: 37633507
pii: S0883-5403(23)00852-5
doi: 10.1016/j.arth.2023.08.046
pmc: PMC10616773
mid: NIHMS1935358
pii:
doi:
Types de publication
Journal Article
Review
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1954-1958Subventions
Organisme : NIAMS NIH HHS
ID : P30 AR076312
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR073147
Pays : United States
Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.
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