Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images.

Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images.
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DOI:
10.1177/0278364914526627
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发表时间:
2014-09
期刊:
The International journal of robotics research
影响因子:
--
通讯作者:
Misra S
Misra S
中科院分区:
其他
文献类型:
--
作者:
Vrooijink GJ;Abayazid M;Patil S;Alterovitz R;Misra S

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针头插入通常在微创医疗程序中进行,如活检和放射癌症治疗。在此类手术中,准确的针尖位置对于正确诊断或成功治疗至关重要。针尖在组织内的准确定位是一项挑战,特别是当目标移动和解剖障碍必须避免时。我们开发了一种针导向系统,能够使用二维(2D)超声图像自主准确地引导可导向针。在三维(3D)非静态环境中,针被引导到一个移动的目标,同时避开移动的障碍物。利用二维超声成像设备,我们的系统精确地跟踪针尖在三维空间中的运动,以估计针尖的姿态。针尖姿态被一个快速探索随机树运动规划器用来计算到目标的可行的针路径。运动规划器的速度足够快,因此可以以闭环的方式重复执行重新规划。这使系统能够纠正针运动中的扰动,以及障碍物和目标位置的运动。我们在软组织幻影中进行的针导向实验获得的最大瞄准误差为0.86±0.35 mm(无障碍物)和2.16±0.88 mm(有移动障碍物)。
Needle insertion is commonly performed in minimally invasive medical procedures such as biopsy and radiation cancer treatment. During such procedures, accurate needle tip placement is critical for correct diagnosis or successful treatment. Accurate placement of the needle tip inside tissue is challenging, especially when the target moves and anatomical obstacles must be avoided. We develop a needle steering system capable of autonomously and accurately guiding a steerable needle using two-dimensional (2D) ultrasound images. The needle is steered to a moving target while avoiding moving obstacles in a three-dimensional (3D) non-static environment. Using a 2D ultrasound imaging device, our system accurately tracks the needle tip motion in 3D space in order to estimate the tip pose. The needle tip pose is used by a rapidly exploring random tree-based motion planner to compute a feasible needle path to the target. The motion planner is sufficiently fast such that replanning can be performed repeatedly in a closed-loop manner. This enables the system to correct for perturbations in needle motion, and movement in obstacle and target locations. Our needle steering experiments in a soft-tissue phantom achieves maximum targeting errors of 0.86 ± 0.35 mm (without obstacles) and 2.16 ± 0.88 mm (with a moving obstacle).