A-SEE: Active-Sensing End-Effector Enabled Probe Self-Normal-Positioning for Robotic Ultrasound Imaging Applications

IF 4.6 2区 计算机科学 Q2 ROBOTICS IEEE Robotics and Automation Letters Pub Date : 2022-10-31 DOI:10.1109/LRA.2022.3218183
Xihan Ma;Wen-Yi Kuo;Kehan Yang;Ashiqur Rahaman;Haichong K. Zhang
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引用次数: 6

Abstract

Conventional manual ultrasound (US) imaging is a physically demanding procedure for sonographers. A robotic US system (RUSS) has the potential to overcome this limitation by automating and standardizing the imaging procedure. It also extends ultrasound accessibility in resource-limited environments with the shortage of human operators by enabling remote diagnosis. During imaging, keeping the US probe normal to the skin surface largely benefits the US image quality. However, an autonomous, real-time, low-cost method to align the probe towards the direction orthogonal to the skin surface without pre-operative information is absent in RUSS. We propose a novel end-effector design to achieve self-normal-positioning of the US probe. The end-effector embeds four laser distance sensors to estimate the desired rotation towards the normal direction. We then integrate the proposed end-effector with a RUSS system which allows the probe to be automatically and dynamically kept to normal direction during US imaging. We evaluated the normal positioning accuracy and the US image quality using a flat surface phantom, an upper torso mannequin, and a lung ultrasound phantom. Results show that the normal positioning accuracy is 4.17 $\pm$ 2.24 degrees on the flat surface and 14.67 $\pm$ 8.46 degrees on the mannequin. The quality of the RUSS collected US images from the lung ultrasound phantom was equivalent to that of the manually collected ones.
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A-SEE:用于机器人超声成像应用的主动传感末端效应器探针自正常定位
传统的手动超声(US)成像对超声医师来说是一种物理要求很高的程序。机器人US系统(RUSS)有可能通过自动化和标准化成像程序来克服这一限制。它还通过实现远程诊断,在资源有限、操作员短缺的环境中扩展了超声波的可访问性。在成像过程中,保持US探头与皮肤表面的法线在很大程度上有利于US图像质量。然而,RUSS中缺乏一种自主、实时、低成本的方法,可以在没有术前信息的情况下将探针对准与皮肤表面正交的方向。我们提出了一种新的末端执行器设计,以实现US探针的自正常定位。末端执行器嵌入四个激光距离传感器,以估计朝向法线方向的期望旋转。然后,我们将所提出的末端执行器与RUSS系统集成,该系统允许探针在US成像期间自动动态地保持在正常方向。我们使用平面体模、上身人体模型和肺部超声体模评估了正常定位精度和US图像质量。结果表明,在平面上的正常定位精度为4.17$\pm$2.24度,在人体模型上为14.67$\pm$8.46度。从肺部超声体模中采集的RUSS US图像的质量与手动采集的图像的质量相当。
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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