ArticleFrontiers in robotics and AI2024
Autonomous ultrasound scanning robotic system based on human posture recognition and image servo control: an application for cardiac imaging.
Article in Frontiers in robotics and AI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Technical challenges in autonomous robotic ultrasound examinations: perception, planning, and control.Journal of robotic surgery · 2026Review
- A Review and Perspective of Techniques for Autonomous Robotic Ultrasound Acquisitions.Sensors (Basel, Switzerland) · 2026Review
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Authors and funding
8 authors.
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Abstract
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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