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Computer Vision in the Operating Room: Opportunities and Caveats.

Authors :
Kennedy-Metz LR
Mascagni P
Torralba A
Dias RD
Perona P
Shah JA
Padoy N
Zenati MA
Source :
IEEE transactions on medical robotics and bionics [IEEE Trans Med Robot Bionics] 2021 Feb; Vol. 3 (1), pp. 2-10. Date of Electronic Publication: 2020 Nov 24.
Publication Year :
2021

Abstract

Effectiveness of computer vision techniques has been demonstrated through a number of applications, both within and outside healthcare. The operating room environment specifically is a setting with rich data sources compatible with computational approaches and high potential for direct patient benefit. The aim of this review is to summarize major topics in computer vision for surgical domains. The major capabilities of computer vision are described as an aid to surgical teams to improve performance and contribute to enhanced patient safety. Literature was identified through leading experts in the fields of surgery, computational analysis and modeling in medicine, and computer vision in healthcare. The literature supports the application of computer vision principles to surgery. Potential applications within surgery include operating room vigilance, endoscopic vigilance, and individual and team-wide behavioral analysis. To advance the field, we recommend collecting and publishing carefully annotated datasets. Doing so will enable the surgery community to collectively define well-specified common objectives for automated systems, spur academic research, mobilize industry, and provide benchmarks with which we can track progress. Leveraging computer vision approaches through interdisciplinary collaboration and advanced approaches to data acquisition, modeling, interpretation, and integration promises a powerful impact on patient safety, public health, and financial costs.

Details

Language :
English
ISSN :
2576-3202
Volume :
3
Issue :
1
Database :
MEDLINE
Journal :
IEEE transactions on medical robotics and bionics
Publication Type :
Academic Journal
Accession number :
33644703
Full Text :
https://doi.org/10.1109/tmrb.2020.3040002