Wiles Andrew D, Likholyot Alexander, Frantz Donald D, Peters Terry M
Imaging Research Laboratories, Robarts Research Institute, London, ON, N6A 5K8 Canada.
IEEE Trans Med Imaging. 2008 Mar;27(3):378-90. doi: 10.1109/TMI.2007.908124.
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 rms tre is provided along with an extension that provides the covariance Sigma tre. 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.
与基于点的医学图像配准问题相关的误差模型最早于20世纪90年代末引入。基准定位误差、基准配准误差和目标配准误差的概念在文献中常用。在由一组彼此刚性固定的基准标记定义的坐标系中，用于估计位置r处目标配准误差的模型在医学成像文献中很常见。该模型也已扩展到模拟光学跟踪工具中感兴趣点处的目标配准误差。然而，该模型仅限于描述在假设基准定位误差在R3中具有各向同性正态分布的情况下的误差。在这项工作中，该模型被推广到包括具有各向异性正态分布的基准定位误差。与先前的模型类似，提供了均方根统计量rms tre以及提供协方差Sigma tre的扩展。新模型通过蒙特卡罗模拟和一组统计假设检验进行验证。最后，在1）光学工具跟踪模拟和2）图像配准的使用背景下，讨论了各向同性和各向异性这两种假设之间的差异。
