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REVIEW article
Front. Surg.
Sec. Colorectal and Proctological Surgery
Volume 12 - 2025 | doi: 10.3389/fsurg.2025.1551838
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With the widespread adoption of minimally invasive surgery, laparoscopic surgery has been an essential component of modern surgical procedures. As key technologies, laparoscopic phase recognition and skill evaluation aim to identify different stages of the surgical process and assess surgeons' operational skills using automated methods. This, in turn, can improve the quality of surgery and the skill of surgeons. This review summarizes the progress of research in laparoscopic surgery, phase recognition, and skill evaluation. At first, the importance of laparoscopic surgery is introduced, clarifying the relationship between phase recognition, skill evaluation, and other surgical tasks. The publicly available surgical datasets for laparoscopic phase recognition tasks are then detailed. The review highlights the research methods that have exhibited superior performance in these public datasets and identifies common characteristics of these highperforming methods. Based on the insights obtained, the commonly used phase recognition research and surgical skill evaluation methods and models in this field are summarized. In addition, this study briefly outlines the standards and methods for evaluating laparoscopic surgical skills. Finally, an analysis of the difficulties researchers face and potential future development directions is presented. Moreover, this paper aims to provide valuable references for researchers, promoting further advancements in this domain.
Keywords: laparoscopic surgery, Phase recognition, skill evaluation, methods, Surgical datasets
Received: 26 Dec 2024; Accepted: 27 Mar 2025.
Copyright: © 2025 Liao, Zhu, Zhang, Wang, Zhang, Chen, Zhou and Ye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zi Ye, Institute of Intelligent Software, Guangzhou 511458, China, Guangzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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