Autonomous Scanning Target Localization for Robotic Lung Ultrasound Imaging

Ma, Xihan; Zhang, Ziming; Zhang, Haichong K.

doi:10.1109/iros51168.2021.9635902

Cited by 24 publications

(5 citation statements)

References 28 publications

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“…Furthermore, since such autonomous systems can separate the patients and clinicians, they can continue providing healthcare intervention, even during infectious pandemics, e.g., COVID-19. Ma et al presented a vision-based framework to automatically perform US examinations of lungs without manual localization [23]. Besides, Hennersperger et al validated the feasibility of autonomous US scans for abdominal application based on a preoperative MRI image [10].…”

Section: B Automatic Robotic Us Acquisitionmentioning

confidence: 99%

Towards Autonomous Atlas-Based Ultrasound Acquisitions in Presence of Articulated Motion

Jiang

Gao

Xie

et al. 2022

IEEE Robot. Autom. Lett.

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Robotic ultrasound (US) imaging aims at overcoming some of the limitations of free-hand US examinations, e.g. difficulty in guaranteeing intra-and inter-operator repeatability. However, due to anatomical and physiological variations between patients and relative movement of anatomical substructures, it is challenging to robustly generate optimal trajectories to examine the anatomies of interest, in particular, when they comprise articulated joints. To address this challenge, this paper proposes a vision-based approach allowing autonomous robotic US limb scanning. To this end, an atlas MRI template of a human arm with annotated vascular structures is used to generate trajectories and register and project them onto patients' skin surfaces for robotic US acquisition. To effectively segment and accurately reconstruct the targeted 3D vessel, we make use of spatial continuity in consecutive US frames by incorporating channel attention modules into a U-Net-type neural network. The automatic trajectory generation method is evaluated on six volunteers with various articulated joint angles. In all cases, the system can successfully acquire the planned vascular structure on volunteers' limbs. For one volunteer the MRI scan was also available, which allows the evaluation of the average radius of the scanned artery from US images, resulting in a radius estimation (1.2±0.05 mm) comparable to the MRI ground truth (1.2 ± 0.04 mm).

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Section: B Automatic Robotic Us Acquisitionmentioning

confidence: 99%

Towards Autonomous Atlas-Based Ultrasound Acquisitions in Presence of Articulated Motion

Jiang

Gao

Xie

et al. 2022

IEEE Robot. Autom. Lett.

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“…During the autonomous US scanning process, the magnitude and variation of contact force significantly impact the quality and stability of US images, as observed by Ipsen et al (2021) . Researchers have proposed various control algorithms to maintain a constant contact force, including impedance control ( Suligoj et al, 2021 ), admittance control ( Tan et al, 2022 ; Wang Z. et al, 2023 ), and PID control ( Ma et al, 2021 ; Zhang et al, 2021 ; 2022 ). Moreover, due to the significant fluctuations in window quality during cardiac US scanning, researchers have introduced several US image servo control algorithms to ensure stable, high-quality imaging.…”

Section: Introductionmentioning

confidence: 99%

Autonomous ultrasound scanning robotic system based on human posture recognition and image servo control: an application for cardiac imaging

Tang,

Wang,

Luo

et al. 2024

Front. Robot. AI

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In traditional cardiac ultrasound diagnostics, the process of planning scanning paths and adjusting the ultrasound window relies solely on the experience and intuition of the physician, a method that not only affects the efficiency and quality of cardiac imaging but also increases the workload for physicians. To overcome these challenges, this study introduces a robotic system designed for autonomous cardiac ultrasound scanning, with the goal of advancing both the degree of automation and the quality of imaging in cardiac ultrasound examinations. The system achieves autonomous functionality through two key stages: initially, in the autonomous path planning stage, it utilizes a camera posture adjustment method based on the human body’s central region and its planar normal vectors to achieve automatic adjustment of the camera’s positioning angle; precise segmentation of the human body point cloud is accomplished through efficient point cloud processing techniques, and precise localization of the region of interest (ROI) based on keypoints of the human body. Furthermore, by applying isometric path slicing and B-spline curve fitting techniques, it independently plans the scanning path and the initial position of the probe. Subsequently, in the autonomous scanning stage, an innovative servo control strategy based on cardiac image edge correction is introduced to optimize the quality of the cardiac ultrasound window, integrating position compensation through admittance control to enhance the stability of autonomous cardiac ultrasound imaging, thereby obtaining a detailed view of the heart’s structure and function. A series of experimental validations on human and cardiac models have assessed the system’s effectiveness and precision in the correction of camera pose, planning of scanning paths, and control of cardiac ultrasound imaging quality, demonstrating its significant potential for clinical ultrasound scanning applications.

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“…With the recent development of collaborative robots, robot-assisted ultrasound scanning has gained significant attention from both the robotics and medical examination communities [2]. This has led to the development of robot-assisted tele-echography systems, which are designed to assist medical experts in acquiring high-quality ultrasound images [3], [4], [5]. There are a number of research works on robot-assisted sonography [6], [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Design and Quantitative Assessment of Teleoperation-Based Human–Robot Collaboration Method for Robot-Assisted Sonography

Si,

Wang,

Yang

2024

IEEE Trans. Automat. Sci. Eng.

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Tele-echography has emerged as a promising and effective solution, leveraging the expertise of sonographers and the autonomy of robots to perform ultrasound scanning for patients residing in remote areas, without the need for in-person visits by the sonographer. Designing effective and natural human-robot interfaces for tele-echography remains challenging, with patient safety being a critical concern. In this article, we develop a teleoperation system for robot-assisted sonography with two different interfaces, a haptic device-based interface and a low-cost 3D Mouse-based interface, which can achieve continuous and intuitive telemanipulation by a leader device with a small workspace. To achieve compliant interaction with patients, we design impedance controllers in Cartesian space to track the desired position and orientation for these two teleoperation interfaces. We also propose comprehensive evaluation metrics of robot-assisted sonography, including subjective and objective evaluation, to evaluate tele-echography interfaces and control performance. We evaluate the ergonomic performance based on the estimated muscle fatigue and the acquired ultrasound image quality. We conduct user studies based on the NASA Task Load Index to evaluate the performance of these two humanrobot interfaces. The tracking performance and the quantitative comparison of these two teleoperation interfaces are conducted by the Franka Emika Panda robot. The results and findings provide guidance on human-robot collaboration design and implementation for robot-assisted sonography.Note to Practitioners-Robot-assisted sonography has demonstrated efficacy in medical diagnosis during clinical trials. However, deploying fully autonomous robots for ultrasound scanning remains challenging due to various constraints in practice, such as patient safety, dynamic tasks, and environmental uncertainties. Semi-autonomous or teleoperation-based robot sonography Manuscript

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Autonomous Scanning Target Localization for Robotic Lung Ultrasound Imaging

Cited by 24 publications

References 28 publications

Towards Autonomous Atlas-Based Ultrasound Acquisitions in Presence of Articulated Motion

Towards Autonomous Atlas-Based Ultrasound Acquisitions in Presence of Articulated Motion

Autonomous ultrasound scanning robotic system based on human posture recognition and image servo control: an application for cardiac imaging

Design and Quantitative Assessment of Teleoperation-Based Human–Robot Collaboration Method for Robot-Assisted Sonography

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