The advances in computer vision that are enabling more autonomous actions in surgery: a systematic review of the literature.

Gumbs, Andrew A.; Grasso, Vincent; Bourdel, Nicolas; Croner, Roland; Spolverato, Gaya; Frigerio, Isabella; Illanes, Alfredo; Abu Hilal, Mohammad; Park, Adrian; Elyan, Eyad

Abstract

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.

Citation

GUMBS, A.A., GRASSO, V., BOURDEL, N., CRONER, R., SPOLVERATO, G., FRIGERIO, I., ILLANES, A., ABU HILAL, M., PARK, A. and ELYAN, E. 2022. The advances in computer vision that are enabling more autonomous actions in surgery: a systematic review of the literature. Sensors [online], 22(13), article 4918. Available from: https://doi.org/10.3390/s22134918

• Journal Article Type: Review
• Acceptance Date: Jun 21, 2022
• Online Publication Date: Jun 29, 2022
• Publication Date: Jul 1, 2022
• Deposit Date: Jul 21, 2022
• Publicly Available Date: Jul 21, 2022
• Journal: Sensors
• Print ISSN: 1424-8220
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 22
• Issue: 13
• Article Number: 4918
• DOI: https://doi.org/10.3390/s22134918
• Keywords: Artificial intelligence surgery; Autonomous actions; Computer vision; Deep learning; Machine learning
• Public URL: https://rgu-repository.worktribe.com/output/1716605