Predictive Camera Tracking for Bronchoscope Simulation with CONDensation
Predictive Camera Tracking for Bronchoscope Simulation with CONDensation
复制标题
通过 CONDensation 进行支气管镜模拟的预测相机跟踪
DOI：
10.1007/11566465_112
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Guang Zhong
中科院分区：
文献类型：
--
作者：
F. Deligianni;A. Chung;Guang Zhong
本文利用时间信息的使用，以尽量减少模糊的摄像机运动跟踪支气管镜模拟。凝聚算法（顺序蒙特卡罗）已被用来传播的状态空间的概率分布。对于运动预测，二阶自回归模型已被用于表征在支气管镜检查中遇到的有界管腔中的相机运动。该方法迎合多模态概率分布，从幻影和患者数据的实验结果表明，跟踪精度显着提高，特别是在有气道变形和图像伪影的情况下。
This paper exploits the use of temporal information to minimize the ambiguity of camera motion tracking in bronchoscope simulation. The condensation algorithm (Sequential Monte Carlo) has been used to propagate the probability distribution of the state space. For motion prediction, a second-order auto-regressive model has been used to characterize camera motion in a bounded lumen as encountered in bronchoscope examination. The method caters for multimodal probability distributions, and experimental results from both phantom and patient data demonstrate a significant improvement in tracking accuracy especially in cases where there is airway deformation and image artefacts.