This paper describes a framework of algorithms for the active localization and tracking of flexible needles and targets during image-guided percutaneous interventions. The needle and target configurations are tracked by Bayesian filters employing models of the needle and target motions and measurements of the current system state obtained from an intra-operative imaging system which is controlled by an entropy-minimizing active localization algorithm. Versions of the system were built using particle and unscented Kalman filters and their performance was measured using both simulations and hardware experiments with real magnetic resonance imaging data of needle insertions into gel phantoms. Performance of the localization algorithms is given in terms of accuracy of the predictions and computational efficiency is discussed.

中文翻译：

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在机器人图像引导干预系统中主动定位和跟踪针头和目标。

本文介绍了在图像引导的经皮介入治疗过程中主动定位和跟踪柔性针头和目标的算法框架。贝叶斯滤波器跟踪针和目标的配置，贝叶斯滤波器采用针和目标运动的模型以及从术中成像系统获得的当前系统状态的测量结果，该术中成像系统由熵最小化的主动定位算法控制。该系统的版本是使用颗粒和无气味的卡尔曼滤波器构建的，并使用模拟和硬件实验以及将针插入凝胶体模中的真实磁共振成像数据来测量其性能。根据预测的准确性给出了定位算法的性能，并讨论了计算效率。