A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets
A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets
复制标题
DOI：
10.1088/0031-9155/54/7/001
复制
发表时间：
2009-04-07
影响因子：
3.5
通讯作者：
Guerrero, Thomas
中科院分区：
文献类型：
--
作者：
Castillo, Richard;Castillo, Edward;Guerrero, Thomas
专家标志对应被广泛报道用于评估可变形图像配准（DEG）的空间精度。在这份报告中，我们提出了一个框架，客观评估的空间精度使用大型专家确定的标志点对。手动生成5个病例的肺标志点对的大样本（> 1100）。通过重复配准确定观察者间和观察者内变异的估计值。对基于梯度的光流算法和基于地标的移动最小二乘算法进行了空间精度的比较评估。空间误差估计的不确定性被认为是成反比的标志点对的数量的平方根和成正比的空间误差的标准偏差。使用该数据的统计特性，我们进行了样本量计算，以估计每种算法的平均空间准确度，95%置信区间在0.5 mm范围内。对于光流和移动最小二乘算法，所需的样本量分别为1050和36。基于少于所需验证标志的比较评估导致相对空间精度的错误表示。这项研究表明，地标对可以用来评估一个狭窄的不确定性范围内的空间精度。
Expert landmark correspondences are widely reported for evaluating deformable image registration (DIR) spatial accuracy. In this report, we present a framework for objective evaluation of DIR spatial accuracy using large sets of expert-determined landmark point pairs. Large samples (> 1100) of pulmonary landmark point pairs were manually generated for five cases. Estimates of inter- and intra-observer variation were determined from repeated registration. Comparative evaluation of DIR spatial accuracy was performed for two algorithms, a gradient-based optical flow algorithm and a landmark-based moving least-squares algorithm. The uncertainty of spatial error estimates was found to be inversely proportional to the square root of the number of landmark point pairs and directly proportional to the standard deviation of the spatial errors. Using the statistical properties of this data, we performed sample size calculations to estimate the average spatial accuracy of each algorithm with 95% confidence intervals within a 0.5 mm range. For the optical flow and moving least-squares algorithms, the required sample sizes were 1050 and 36, respectively. Comparative evaluation based on fewer than the required validation landmarks results in misrepresentation of the relative spatial accuracy. This study demonstrates that landmark pairs can be used to assess DIR spatial accuracy within a narrow uncertainty range.