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

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SENSORS
卷 22, 期 13, 页码 -

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MDPI
DOI: 10.3390/s22134918

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artificial intelligence surgery; autonomous actions; computer vision; deep learning; machine learning

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This review focuses on the advances and limitations of computer vision in surgery and discusses how it can contribute to achieving more autonomous actions. It also highlights the use of non-visual data in aiding robotic autonomy and addresses the current crisis regarding autonomy in surgical procedures.
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.

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