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Estimation Methods of Flexible Tip-Steerable Needles: A Comparative Study

机译:指尖可弯曲针的估计方法:比较研究

摘要

Needle insertion was used in percutaneous procedures such as biopsies and brachytherapy. Flexible Needles has attracted many attentions for its advantages in obstacle avoidance. In order to make the flexible needle reach the target position, the position and attitude of the flexible needle must be estimated. This paper uses three different non-linear estimation methods to estimate the st1ate of the flexible needle. The first one is the most commonly used extended kalman filter (EKF), the second is unscented kalman filter (UKF), the last one is the particle filter (PF). Principle, complexity and characteristic of the three estimation methods is different. In this paper, these different kind of filters is applied in the flexible needle with a comparative analysis. The uncertainty of the bevel-up needle model is not only reflected in the noises which these filters mainly deal with, but also the uncertainty of the model parameter. In this paper, the model parameter error is also considered. Kalman filter is based on the Gaussian noises. In this paper, we consider the situation of non-Gaussian noises.
机译:在经皮手术(例如活检和近距离放射治疗)中使用了针头插入。柔性针在避障方面的优势吸引了众多关注。为了使柔性针到达目标位置,必须估计柔性针的位置和姿势。本文使用三种不同的非线性估计方法来估计柔性针的状态。第一个是最常用的扩展卡尔曼滤波器(EKF),第二个是无味卡尔曼滤波器(UKF),最后一个是粒子滤波器(PF)。三种估计方法的原理,复杂度和特性不同。本文通过对比分析将这些不同类型的过滤器应用于柔性针头。斜针模型的不确定性不仅反映在这些滤波器主要处理的噪声中,还反映在模型参数的不确定性上。本文还考虑了模型参数误差。卡尔曼滤波器基于高斯噪声。在本文中,我们考虑了非高斯噪声的情况。

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