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Fast vision-based catheter 3D reconstruction

机译:基于快速视觉的导管3D重建

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Continuum robots offer better maneuverability and inherent compliance and are well-suited for surgical applications as catheters, where gentle interaction with the environment is desired. However, sensing their shape and tip position is a challenge as traditional sensors can not be employed in the way they are in rigid robotic manipulators. In this paper, a high speed vision-based shape sensing algorithm for real-time 3D reconstruction of continuum robots based on the views of two arbitrary positioned cameras is presented. The algorithm is based on the closed-form analytical solution of the reconstruction of quadratic curves in 3D space from two arbitrary perspective projections. High-speed image processing algorithms are developed for the segmentation and feature extraction from the images. The proposed algorithms are experimentally validated for accuracy by measuring the tip position, length and bending and orientation angles for known circular and elliptical catheter shaped tubes. Sensitivity analysis is also carried out to evaluate the robustness of the algorithm. Experimental results demonstrate good accuracy (maximum errors of +/- 0.6 mm and +/- 0.5 deg), performance (200 Hz), and robustness (maximum absolute error of 1.74 mm, 3.64 deg for the added noises) of the proposed high speed algorithms.
机译:连续机器人具有更好的可操纵性和固有的柔顺性,非常适合作为导管的外科应用,需要与环境进行柔和的交互。然而,感测它们的形状和尖端位置是一个挑战,因为传统的传感器无法像在刚性机器人操纵器中那样采用。在本文中,提出了一种基于高速视觉的形状感测算法,该算法基于两个任意定位的摄像机的视图进行连续体机器人的实时3D重建。该算法基于从两个任意透视图投影在3D空间中重建二次曲线的闭合形式解析解。开发了高速图像处理算法,用于图像的分割和特征提取。通过测量已知圆形和椭圆形导管形状的尖端的位置,长度以及弯曲角度和定向角度,通过实验验证了所提出算法的准确性。还进行了灵敏度分析,以评估算法的鲁棒性。实验结果表明,所建议的高速传感器具有良好的精度(最大误差为+/- 0.6 mm和+/- 0.5度),性能(200 Hz)和鲁棒性(最大绝对误差为1.74 mm,附加噪声为3.64度)算法。

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