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REVIEW article
Front. Surg.
Sec. Visceral Surgery
Volume 12 - 2025 | doi: 10.3389/fsurg.2025.1557153
Vision Techniques for Anatomical Structures in Laparoscopic Surgery: A Comprehensive Review
Provisionally accepted
Ru Zhou 1
Dan Wang 2
Hanwei ZHANG 3
Ying Zhu 2
Lijun Zhang 4 Tianxiang Chen 5 Wenqiang Liao 1
Zi Ye 3*- 1 Department of General Surgery, RuiJin Hospital LuWan Branch, Shanghai Jiaotong University School of Medicine, Shanghai, China
- 2 Hangzhou Institute for Advanced Study, University of Chinese Academy of Science, Hangzhou, China
- 3 Institute of Intelligent Software, Guangzhou, China
- 4 Institute of Software Chinese Academy of Sciences, Beijing, China
- 5 University of Science and Technology of China, Hefei, Anhui Province, China
Laparoscopic surgery is the method of choice for numerous surgical procedures, while it confronts a lot of challenges. Computer vision exerts a vital role in addressing these challenges and has become a research hotspot, especially in the classification, segmentation, and target detection of abdominal anatomical structures. This study presents a comprehensive review of the last decade of research in this area. At first, a categorized overview of the core subtasks is presented regarding their relevance and applicability to real-world medical scenarios. Second, the dataset used in the experimental validation is statistically analyzed. Subsequently, the technical approaches and trends of classification, segmentation, and target detection tasks are explored in detail, highlighting their advantages, limitations, and practical implications. Additionally, evaluation methods for the three types of tasks are discussed. Finally, gaps in current research are identified.Meanwhile, the great potential for development in this area is emphasized.
Keywords: Computer Vision, laparoscopic surgery, segmentation, Classification, object detection
Received: 08 Jan 2025; Accepted: 17 Mar 2025.
Copyright: © 2025 Zhou, Wang, ZHANG, Zhu, Zhang, Chen, Liao 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, 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.