{"title":"MCPD-YOLOv3: A Novel Lightweight Detection Model for Surgical Instruments in Laparoscopic Images","authors":"Yuqin Li, Chuqi Li, Ke Zhang, Yu Miao, Weili Shi, Zhengang Jiang","doi":"10.1002/rcs.70104","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Laparoscopic surgical instruments detection is necessary in computer-aided minimally invasive surgery. Most current methods suffer from unsatisfied performance and low detection speed.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>In this paper, a framework called MCPD-YOLOv3 is proposed to balance the efficiency and effectiveness of laparoscopic surgical instruments detection. It effectively fuses feature maps using a parallel manner, and adopts various lightweight strategies to design a lightweight model. Besides, DIoU is employed to improve the recall performance.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The proposed method achieved the mAP of 99.47% and 97.65% at 49.81 FPS for the ATLAS Dione and m2cai16-tool-locations datasets, respectively, with a compact model size of 12.4M and a low FLOPs count of 7.44G.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>These results highlight that MCPD-YOLOv3 excels in high detection performance and rapid response. The model's efficiency in parameter size and FLOPs demonstrates its suitability for applications requiring rapid processing and precise detection, making it a valuable tool for real-time surgical instrument detection in challenging environments.</p>\n </section>\n </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":"21 4","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Medical Robotics and Computer Assisted Surgery","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rcs.70104","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Laparoscopic surgical instruments detection is necessary in computer-aided minimally invasive surgery. Most current methods suffer from unsatisfied performance and low detection speed.
Methods
In this paper, a framework called MCPD-YOLOv3 is proposed to balance the efficiency and effectiveness of laparoscopic surgical instruments detection. It effectively fuses feature maps using a parallel manner, and adopts various lightweight strategies to design a lightweight model. Besides, DIoU is employed to improve the recall performance.
Results
The proposed method achieved the mAP of 99.47% and 97.65% at 49.81 FPS for the ATLAS Dione and m2cai16-tool-locations datasets, respectively, with a compact model size of 12.4M and a low FLOPs count of 7.44G.
Conclusion
These results highlight that MCPD-YOLOv3 excels in high detection performance and rapid response. The model's efficiency in parameter size and FLOPs demonstrates its suitability for applications requiring rapid processing and precise detection, making it a valuable tool for real-time surgical instrument detection in challenging environments.
期刊介绍:
The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.