Scanning Path Planning of the Robot for Breast Ultrasound Examination Based on Binocular Vision and NURBS

Zhang, Xinran; Zhang, Yongde; Du, Haiyan; Lu, Mingyue; Zhao, Zixi; Zhang, Yanhua; Zuo, Sihao

doi:10.1109/access.2022.3196774

Cited by 4 publications

(1 citation statement)

References 36 publications

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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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