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IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering最新文献

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Particle Filter Based Active Localization of Target and Needle in Robotic Image-Guided Intervention Systems. 基于粒子滤波的机器人图像引导干预系统中目标和指针的主动定位。
Mark Renfrew, Zhuofu Bai, M Cenk Cavuşoğlu

This paper presents a probabilistic method for active localization of needle and targets in robotic image guided interventions. Specifically, an active localization scenario where the system directly controls the imaging system to actively localize the needle and target locations using intra-operative medical imaging (e.g., computerized tomography and ultrasound imaging) is explored. In the proposed method, the active localization problem is posed as an information maximization problem, where the beliefs for the needle and target states are represented and estimated using particle filters. The proposed method is also validated using a simulation study.

提出了一种机器人图像引导干预中针和目标主动定位的概率方法。具体而言,探索了一种主动定位场景,即系统直接控制成像系统,利用术中医学成像(如计算机断层扫描和超声成像)主动定位针头和目标位置。在该方法中,将主动定位问题转化为信息最大化问题,利用粒子滤波器表示和估计针和目标状态的信念。通过仿真研究验证了该方法的有效性。
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引用次数: 8
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IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering
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