首页> 外文期刊>IEEE Robotics and Automation Letters >Automatic Normal Positioning of Robotic Ultrasound Probe Based Only on Confidence Map Optimization and Force Measurement
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Automatic Normal Positioning of Robotic Ultrasound Probe Based Only on Confidence Map Optimization and Force Measurement

机译:仅基于置信地图优化和力测量基于机器人超声探头的自动正常定位

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Acquiring good image quality is one of the main challenges for fully-automatic robot-assisted ultrasound systems (RUSS). The presented method aims at overcoming this challenge for orthopaedic applications by optimizing the orientation of the robotic ultrasound (US) probe, i.e. aligning the central axis of the US probe to the tissue's surface normal at the point of contact in order to improve sound propagation within the tissue. We first optimize the in-plane orientation of the probe by analyzing the confidencemap of theUS image. We then carry out a fanmotion and analyze the resulting forces estimated from joint torques to align the central axis of the probe to the normal within the plane orthogonal to the initial image plane. This results in the final 3D alignment of the probe's main axis with the normal to the anatomical surface at the point of contact without using external sensors for surface reconstruction or localizing the point of contact in an anatomical atlas. The algorithm is evaluated both on a phantom and on human tissues (forearm, upper arm and lower back). The mean absolute angular difference (+/- STD) between true and estimated normal on stationary phantom, forearm, upper arm and lower back was 3.1 +/- 1.0., 3.7 +/- 1.7., 5.3 +/- 1.3. and 6.9 +/- 3.5., respectively. In comparison, six human operators obtained errors of 3.2 +/- 1.7. on the phantom. Hence themethod is able to automatically position the probe normal to the scanned tissue at the point of contact and thus improve the quality of automatically acquired ultrasound images.
机译:获得良好的图像质量是全自动机器人辅助超声系统(RUS)的主要挑战之一。本方法旨在通过优化机器人超声(US)探针的方向,即使US探针的中心轴在接触点处对组织表面正常的阵列来克服矫形应用,以改善内部的声音传播组织。我们首先通过分析函授图像的ConfidenceMap来优化探测的面内取向。然后,我们进行煽动和分析从联合扭矩估计的所得力,以将探头的中心轴与初始图像平面正交的平面内的正常。这导致探针的主轴的最终3D对准,在接触点处具有正常的解剖表面,而不使用外部传感器进行表面重建或定位解剖图中的接触点。该算法在幻影和人体组织上进行评估(前臂,上臂和腰部)。真实和估计的固定模型,前臂,上臂和腰部正常的平均绝对角差(+/- STD)为3.1 +/- 1.0。,3.7 +/- 1.7。,5.3 +/- 1.3。和6.9 +/- 3.5。分别为。相比之下,六人运营商获得了3.2 +/- 1.7的误差。在幻影上。因此,在接触点处能够自动将探头正常定位到扫描的组织,从而提高自动获取超声图像的质量。

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