Bevel-tip steerable needles for percutaneous intervention are prone to torsion determined by the interaction forces with the human tissue. If disregarded, torsion can affect the insertion accuracy inducing a change in the needle tip orientation, which is generally undetectable by tracking devices because of the small diameter of the needle. This letter presents a method for estimating the tip pose (i.e. position and orientation) of a programmable bevel-tip needle using a 2-D kinematic based Extended Kalman Filter (EKF), where the tip position of the two steering segments is used as input measurement. Simulation trials and experiments in phantom-brain gelatin were performed to prove the performance of the method and mimic real case scenarios. The solution presented shows state-of-the-art performance in needle pose estimation with a bounded positional error of $< \!\text{1 mm}$ and orientation error of $< \!\text{5}^{\circ }$.

中文翻译：

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基于模型的多段可编程斜尖可操纵针的稳健姿态估计

用于经皮介入的斜尖可操纵针容易发生扭转，这是由与人体组织的相互作用力决定的。如果不考虑，扭转会影响插入精度，从而导致针尖方向的变化，由于针的直径很小，跟踪装置通常无法检测到这种变化。这封信提出了一种使用基于 2-D 运动学的扩展卡尔曼滤波器 (EKF) 来估计可编程斜尖针的尖端姿势（即位置和方向）的方法，其中两个转向段的尖端位置用作输入测量。在幻脑明胶中进行了模拟试验和实验，以证明该方法的性能并模拟真实案例场景。$< \!\text{1 毫米}$ 和方向误差 $< \!\text{5}^{\circ }$.