Semi-Automated Needle Steering in Biological Tissue Using an Ultrasound-Based Deflection Predictor
Semi-Automated Needle Steering in Biological Tissue Using an Ultrasound-Based Deflection Predictor
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DOI：
10.1007/s10439-016-1736-x
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发表时间：
2017-04-01
影响因子：
3.8
通讯作者：
Tavakoli, Mahdi
中科院分区：
文献类型：
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作者：
Khadem, Mohsen;Rossa, Carlos;Tavakoli, Mahdi
基于针的介入操作的性能取决于针尖定位的准确性。在此，提出了一种新颖的针操控策略，可提高针操控的准确性。在我们的方法中，外科医生负责进针以确保手术安全，而针尖斜面位置由机器人控制以将靶向误差降至最低。该系统有两个主要组成部分：（1）一个实时预测器，用于在针在软组织内被操控时估计其未来的弯曲情况，以及（2）一个在线运动规划器，它通过对针弯曲预测的迭代优化来计算控制决策并将针导向目标。该预测器利用基于超声的曲率信息来估计针的弯曲。给定术前图像中的解剖障碍物和目标的规格，运动规划器利用弯曲预测来估计控制动作，即针应旋转的深度以到达目标。在有障碍物和无障碍物的情况下进行体外进针实验以验证我们的方法。结果表明，针操控策略可将针引导至目标，最大误差为1.22毫米。
The performance of needle-based interventions depends on the accuracy of needle tip positioning. Here, a novel needle steering strategy is proposed that enhances accuracy of needle steering. In our approach the surgeon is in charge of needle insertion to ensure the safety of operation, while the needle tip bevel location is robotically controlled to minimize the targeting error. The system has two main components: (1) a real-time predictor for estimating future needle deflection as it is steered inside soft tissue, and (2) an online motion planner that calculates control decisions and steers the needle toward the target by iterative optimization of the needle deflection predictions. The predictor uses the ultrasound-based curvature information to estimate the needle deflection. Given the specification of anatomical obstacles and a target from preoperative images, the motion planner uses the deflection predictions to estimate control actions, i.e., the depth(s) at which the needle should be rotated to reach the target. Ex-vivo needle insertions are performed with and without obstacle to validate our approach. The results demonstrate the needle steering strategy guides the needle to the targets with a maximum error of 1.22 mm.