Skip to main content

ORIGINAL RESEARCH article

Front. Robot. AI
Sec. Biomedical Robotics
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1527686

Autonomous Robotic Ultrasound Scanning System: A Key to Enhancing Image Analysis Reproducibility and Observer Consistency in Ultrasound Imaging

Provisionally accepted
Ming-De Li Ming-De Li 1Xin-Xin Lin Xin-Xin Lin 1Si Min Ruan Si Min Ruan 1Wei-Ping Ke Wei-Ping Ke 1Hao-Ruo Zhang Hao-Ruo Zhang 2Hui Huang Hui Huang 1Shao-Hong Wu Shao-Hong Wu 1Mei-Qing Cheng Mei-Qing Cheng 1Wen-Juan Tong Wen-Juan Tong 1Hang-Tong Hu Hang-Tong Hu 1Dan-Ni He Dan-Ni He 3Rui-Fang Lu Rui-Fang Lu 1Ya-Dan Lin Ya-Dan Lin 4Ming Kuang Ming Kuang 1Ming-de Lu Ming-de Lu 1Li-da Chen Li-da Chen 1Qinghua Huang Qinghua Huang 2,5Wei Wang Wei Wang 1*
  • 1 The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
  • 2 College of Electronic Information, Guangxi Minzu University, Nanning,, Guangx, China
  • 3 Department of Ultrasound Department, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
  • 4 Department of Ultrasound, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi Zhuang Region, China
  • 5 Northwestern Polytechnical University, Xi'an, Shaanxi Province, China

The final, formatted version of the article will be published soon.

    Purpose: This study aims to develop an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline, comparing its reproducibility and observer consistency in image analysis with physicians of varying levels of expertise.Design/methodology/approach: An auto-RUSS was engineered using a 7-degree-of-freedom robotic arm, with real-time regulation based on force control and ultrasound visual servoing. Two phantoms were employed for the human-machine comparative experiment, involving three groups: auto-RUSS, non-expert (4 junior physicians), and expert (4 senior physicians). This setup enabled comprehensive assessment of reproducibility in contact force, image acquisition, image measurement and AI-assisted classification. Radiological feature variability was measured using the coefficient of variation (COV), while performance and reproducibility assessments utilized mean and standard deviation (SD).Findings: The auto-RUSS had the potential to reduce operator-dependent variability in ultrasound examinations, offering enhanced repeatability and consistency across multiple dimensions including probe contact force, images acquisition, image measurement, and diagnostic model performance.Originality/value: In this paper, an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline was proposed. Through comprehensive human-machine comparison experiments, the auto-RUSS was shown to effectively improve the reproducibility of ultrasound images and minimize human-induced variability.

    Keywords: Autonomous Robots, ultrasound, reproducibility, Consistency, AI

    Received: 13 Nov 2024; Accepted: 17 Jan 2025.

    Copyright: © 2025 Li, Lin, Ruan, Ke, Zhang, Huang, Wu, Cheng, Tong, Hu, He, Lu, Lin, Kuang, Lu, Chen, Huang and Wang. 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: Wei Wang, The First Affiliated Hospital of Sun Yat-sen University, 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.