A Statistical Model for Point-Based Target Registration Error With Anisotropic Fiducial Localizer Error
A Statistical Model for Point-Based Target Registration Error With Anisotropic Fiducial Localizer Error
复制标题
具有各向异性基准定位器误差的基于点的目标配准误差统计模型
DOI：
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发表时间：
2008
影响因子：
10.6
通讯作者：
T. Peters
中科院分区：
文献类型：
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作者：
Andrew D. Wiles;Alexander Likholyot;Donald D Frantz;T. Peters
与基于点的医学图像配准问题相关的误差模型是在20世纪90年代末首次引入的。文献中常用的概念有基准定位误差、基准配准误差和目标配准误差。在一组相对固定的基准标记所定义的坐标系中，在位置r处估计目标配准误差的模型在医学成像文献中普遍存在。该模型还扩展到模拟光学跟踪工具中感兴趣点的目标配准误差。然而，该模型仅限于在假设基准定位器误差在R3中具有各向同性正态分布的情况下描述误差。在这项工作中，该模型被推广到包含具有各向异性正态分布的基准定位器误差。与前面的模型类似，均方根统计量rmstre与提供协方差矩阵Sigmatre的扩展一起提供。利用蒙特卡罗模拟和一组统计假设检验对新模型进行了验证。最后，在1)光学工具跟踪仿真和2)图像配准的背景下，讨论了两种假设（各向同性和各向异性）之间的差异。
Error models associated with point-based medical image registration problems were first introduced in the late 1990s. The concepts of fiducial localizer error, fiducial registration error, and target registration error are commonly used in the literature. The model for estimating the target registration error at a position r in a coordinate frame defined by a set of fiducial markers rigidly fixed relative to one another is ubiquitous in the medical imaging literature. The model has also been extended to simulate the target registration error at the point of interest in optically tracked tools. However, the model is limited to describing the error in situations where the fiducial localizer error is assumed to have an isotropic normal distribution in R3. In this work, the model is generalized to include a fiducial localizer error that has an anisotropic normal distribution. Similar to the previous models, the root mean square statistic rmstre is provided along with an extension that provides the covariance matrix Sigmatre. The new model is verified using a Monte Carlo simulation and a set of statistical hypothesis tests. Finally, the differences between the two assumptions, isotropic and anisotropic, are discussed within the context of their use in 1) optical tool tracking simulation and 2) image registration.