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Review

The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature

1
Departement de Chirurgie Digestive, Centre Hospitalier Intercommunal de, Poissy/Saint-Germain-en-Laye, 78300 Poissy, France
2
Department of Surgery, University of Magdeburg, 39106 Magdeburg, Germany
3
Family Christian Health Center, 31 West 155th St., Harvey, IL 60426, USA
4
Gynecological Surgery Department, CHU Clermont Ferrand, 1, Place Lucie-Aubrac Clermont-Ferrand, 63100 Clermont-Ferrand, France
5
EnCoV, Institut Pascal, UMR6602 CNRS, UCA, Clermont-Ferrand University Hospital, 63000 Clermont-Ferrand, France
6
SurgAR-Surgical Augmented Reality, 63000 Clermont-Ferrand, France
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Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, 35122 Padova, Italy
8
Department of Hepato-Pancreato-Biliary Surgery, Pederzoli Hospital, 37019 Peschiera del Garda, Italy
9
INKA-Innovation Laboratory for Image Guided Therapy, Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany
10
Unità Chirurgia Epatobiliopancreatica, Robotica e Mininvasiva, Fondazione Poliambulanza Istituto Ospedaliero, Via Bissolati, 57, 25124 Brescia, Italy
11
Anne Arundel Medical Center, Johns Hopkins University, Annapolis, MD 21401, USA
12
School of Computing, Robert Gordon University, Aberdeen AB10 7JG, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Marco Leo
Sensors 2022, 22(13), 4918; https://doi.org/10.3390/s22134918
Received: 20 May 2022 / Revised: 21 June 2022 / Accepted: 21 June 2022 / Published: 29 June 2022
(This article belongs to the Special Issue Robotics in Healthcare: Automation, Sensing and Application)
This is a review focused on advances and current limitations of computer vision (CV) and how CV can help us obtain to more autonomous actions in surgery. It is a follow-up article to one that we previously published in Sensors entitled, “Artificial Intelligence Surgery: How Do We Get to Autonomous Actions in Surgery?” As opposed to that article that also discussed issues of machine learning, deep learning and natural language processing, this review will delve deeper into the field of CV. Additionally, non-visual forms of data that can aid computerized robots in the performance of more autonomous actions, such as instrument priors and audio haptics, will also be highlighted. Furthermore, the current existential crisis for surgeons, endoscopists and interventional radiologists regarding more autonomy during procedures will be discussed. In summary, this paper will discuss how to harness the power of CV to keep doctors who do interventions in the loop. View Full-Text
Keywords: artificial intelligence surgery; autonomous actions; computer vision; deep learning; machine learning artificial intelligence surgery; autonomous actions; computer vision; deep learning; machine learning
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MDPI and ACS Style

Gumbs, A.A.; Grasso, V.; Bourdel, N.; Croner, R.; Spolverato, G.; Frigerio, I.; Illanes, A.; Abu Hilal, M.; Park, A.; Elyan, E. The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature. Sensors 2022, 22, 4918. https://doi.org/10.3390/s22134918

AMA Style

Gumbs AA, Grasso V, Bourdel N, Croner R, Spolverato G, Frigerio I, Illanes A, Abu Hilal M, Park A, Elyan E. The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature. Sensors. 2022; 22(13):4918. https://doi.org/10.3390/s22134918

Chicago/Turabian Style

Gumbs, Andrew A., Vincent Grasso, Nicolas Bourdel, Roland Croner, Gaya Spolverato, Isabella Frigerio, Alfredo Illanes, Mohammad Abu Hilal, Adrian Park, and Eyad Elyan. 2022. "The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature" Sensors 22, no. 13: 4918. https://doi.org/10.3390/s22134918

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