Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands.
Med Image Anal. 2011 Feb;15(1):71-84. doi: 10.1016/j.media.2010.07.005. Epub 2010 Aug 3.
Quantitative evaluation of image registration algorithms is a difficult and under-addressed issue due to the lack of a reference standard in most registration problems. In this work a method is presented whereby detailed reference standard data may be constructed in an efficient semi-automatic fashion. A well-distributed set of n landmarks is detected fully automatically in one scan of a pair to be registered. Using a custom-designed interface, observers define corresponding anatomic locations in the second scan for a specified subset of s of these landmarks. The remaining n-s landmarks are matched fully automatically by a thin-plate-spline based system using the s manual landmark correspondences to model the relationship between the scans. The method is applied to 47 pairs of temporal thoracic CT scans, three pairs of brain MR scans and five thoracic CT datasets with synthetic deformations. Interobserver differences are used to demonstrate the accuracy of the matched points. The utility of the reference standard data as a tool in evaluating registration is shown by the comparison of six sets of registration results on the 47 pairs of thoracic CT data.
由于在大多数配准问题中缺乏参考标准，因此对图像配准算法进行定量评估是一个困难且未得到充分解决的问题。在这项工作中，提出了一种方法，通过该方法可以以高效的半自动方式构建详细的参考标准数据。在要注册的一对扫描中，自动检测到一组分布良好的 n 个地标。使用定制的界面，观察者为这些地标中的指定子集 s 定义第二个扫描中的相应解剖位置。其余的 n-s 地标通过基于薄板样条的系统自动匹配，该系统使用 s 个手动地标对应来模拟扫描之间的关系。该方法应用于 47 对时间胸部 CT 扫描、3 对脑 MR 扫描和 5 个具有合成变形的胸部 CT 数据集。通过比较 47 对胸部 CT 数据上的六组配准结果，利用观察者间的差异来证明匹配点的准确性。通过将六组配准结果与 47 对胸部 CT 数据进行比较，展示了参考标准数据作为评估配准工具的效用。
