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Lin XX, Li MD, Ruan SM, Ke WP, Zhang HR, Huang H, Wu SH, Cheng MQ, Tong WJ, Hu HT, He DN, Lu RF, Lin YD, Kuang M, Lu MD, Chen LD, Huang QH, Wang W. Autonomous robotic ultrasound scanning system: a key to enhancing image analysis reproducibility and observer consistency in ultrasound imaging. Front Robot AI 2025; 12:1527686. [PMID: 39975565 PMCID: PMC11835693 DOI: 10.3389/frobt.2025.1527686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2024] [Accepted: 01/17/2025] [Indexed: 02/21/2025] Open
Abstract
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.
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Affiliation(s)
- Xin-Xin Lin
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ming-De Li
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Si-Min Ruan
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wei-Ping Ke
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Hao-Ruo Zhang
- College of Electronic Information, Guangxi Minzu University, Nanning, China
| | - Hui Huang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Shao-Hong Wu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Mei-Qing Cheng
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wen-Juan Tong
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Hang-Tong Hu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Dan-Ni He
- Department of Medical Ultrasonics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Rui-Fang Lu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ya-Dan Lin
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Ming Kuang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ming-De Lu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Li-Da Chen
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Qing-Hua Huang
- College of Electronic Information, Guangxi Minzu University, Nanning, China
- School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, Shaanxi, China
| | - Wei Wang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Shabir D, Anjum A, Hamza H, Padhan J, Al-Ansari A, Yaacoub E, Mohammed A, Navkar NV. Development and Evaluation of a Mixed-Reality Tele-ultrasound System. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:1867-1874. [PMID: 37263893 DOI: 10.1016/j.ultrasmedbio.2023.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/25/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023]
Abstract
OBJECTIVE The objective of this feasibility study was to develop and assess a tele-ultrasound system that would enable an expert sonographer (situated at the remote site) to provide real-time guidance to an operator (situated at the imaging site) using a mixed-reality environment. METHODS An architecture along with the operational workflow of the system is designed and a prototype is developed that enables guidance in form of audiovisual cues. The visual cues comprise holograms (of the ultrasound images and ultrasound probe) and is rendered to the operator using a head-mounted display device. The position and orientation of the ultrasound probe's hologram are remotely controlled by the expert sonographer and guide the placement of a physical ultrasound probe at the imaging site. The developed prototype was evaluated for its performance on a network. In addition, a user study (with 12 participants) was conducted to assess the operator's ability to align the probe under different guidance modes. RESULTS The network performance revealed the view of the imaging site and ultrasound images were transferred to the remote site in 233 ± 42 and 158 ± 38 ms, respectively. The expert sonographer was able to transfer, to the imaging site, data related to position and orientation of the ultrasound probe's hologram in 78 ± 13 ms. The user study indicated that the audiovisual cues are sufficient for an operator to position and orient a physical probe for accurate depiction of the targeted tissue (p < 0.001). The probe's placement translational and rotational errors were 1.4 ± 0.6 mm and 5.4 ± 2.2º. CONCLUSION The work illustrates the feasibility of using a mixed-reality environment for effective communication between an expert sonographer (ultrasound physician) and an operator. Further studies are required to determine its applicability in a clinical setting during tele-ultrasound.
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Affiliation(s)
- Dehlela Shabir
- Department of Surgery, Hamad Medical Corporation, Doha, Qatar
| | - Arshak Anjum
- Department of Computer Science and Engineering, Qatar University, Doha, Qatar
| | - Hawa Hamza
- Department of Surgery, Hamad Medical Corporation, Doha, Qatar
| | | | | | - Elias Yaacoub
- Department of Computer Science and Engineering, Qatar University, Doha, Qatar
| | - Amr Mohammed
- Department of Computer Science and Engineering, Qatar University, Doha, Qatar
| | - Nikhil V Navkar
- Department of Surgery, Hamad Medical Corporation, Doha, Qatar.
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Khorasani M, Abdurahiman N, Padhan J, Zhao H, Al-Ansari A, Becker AT, Navkar N. Preliminary design and evaluation of a generic surgical scope adapter. Int J Med Robot 2023; 19:e2475. [PMID: 36288569 DOI: 10.1002/rcs.2475] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 08/21/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Robotic scope assistant systems are used to visualise and navigate the operative field during a laparoscopic surgery. The objective of this work is to design a surgical scope adapter that enables control of different scope types (zero-degree, angulated, and articulated), and can be connected to any six degree-of-freedom robotic manipulator for usage as a robotic scope assistant system. METHODS A surgical scope adapter compatible with different camera heads and scope types was designed and prototyped. The technical performance of the scope adapter was evaluated and a user study was conducted to assess the human-in-the-loop control. RESULTS All the subjects were able to navigate the simulated operative field. The scope adapter permits continuous motion to explore the operative field as well as intermittent motion to accurately focus on the targeted anatomical landmarks. CONCLUSION The modular and generic nature of the surgical scope adapter may enable its usage across different minimally invasive surgeries.
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Affiliation(s)
| | | | | | - Haoran Zhao
- Department of Electrical and Computer Engineering, University of Houston, Houston, Texas, USA
| | | | - Aaron T Becker
- Department of Electrical and Computer Engineering, University of Houston, Houston, Texas, USA
| | - Nikhil Navkar
- Department of Surgery, Hamad Medical Corporation, Doha, Qatar
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Bao X, Wang S, Zheng L. A Novel Ultrasound Robot with Force/torque Measurement and Control for Safe and Efficient Scanning. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023; 72:1-12. [PMID: 37323850 PMCID: PMC7614653 DOI: 10.1109/tim.2023.3239925] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Medical ultrasound is of increasing importance in medical diagnosis and intraoperative assistance and possesses great potential advantages when integrated with robotics. However, some concerns, including the operation efficiency, operation safety, image quality, and comfort of patients, remain after introducing robotics into medical ultrasound. In this paper, an ultrasound robot integrating a force control mechanism, force/torque measurement mechanism, and online adjustment method, is proposed to overcome the current limitations. The ultrasound robot can measure operating forces and torques, provide adjustable constant operating forces, eliminate great operating forces introduced by accidental operations, and achieve various scanning depths based on clinical requirements. The proposed ultrasound robot would potentially facilitate sonographers to find the targets quickly, improve operation safety and efficiency, and decrease patients' discomfort. Simulations and experiments were carried out to evaluate the performance of the ultrasound robot. Experimental results show that the proposed ultrasound robot is able to detect operating force in the z-direction and torques around the x- and y- directions with errors of 3.53% F.S., 6.68% F.S., and 6.11% F.S., respectively, maintain the constant operating force with errors of less than 0.57N, and achieve various scanning depths for target searching and imaging. This proposed ultrasound robot has good performance and would potentially be used in medical ultrasound.
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Affiliation(s)
- Xianqiang Bao
- School of Biomedical Engineering & Imaging Sciences, King’s College London, SE1 7EH, United Kingdom
| | - Shuangyi Wang
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Lingling Zheng
- Faculty of Engineering and Design, Kagawa University, Takamatsu 761-0396, Japan
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