IEEE Trans Med Imaging. 2014 Feb;33(2):422-32. doi: 10.1109/TMI.2013.2286192. Epub 2013 Oct 17.
Nonrigid image registration techniques using intensity based similarity measures are widely used in medical imaging applications. Due to high computational complexities of these techniques, particularly for volumetric images, finding appropriate registration methods to both reduce the computation burden and increase the registration accuracy has become an intensive area of research. In this paper, we propose a fast and accurate nonrigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find the important regions for registration and use an appropriate sampling scheme to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments on registration of end-inhale to end-exhale lung CT scan pairs, with expert annotated landmarks, show that the new method is both faster and more accurate than the state of the art sampling based techniques, particularly for registration of images with large deformations.
基于强度相似度的非刚性图像配准技术在医学成像应用中得到了广泛的应用。由于这些技术的计算复杂度很高，特别是对于容积图像，寻找合适的配准方法来降低计算负担并提高配准精度已成为一个研究热点。在本文中，我们提出了一种用于同模态容积图像的快速准确的非刚性配准方法。我们的方法利用基于有序统计的分割方法提供的信息，找到用于配准的重要区域，并使用适当的采样方案来针对这些区域，从而减少配准的计算时间。所提出的方法的一个独特优势是其能够识别收益递减点并停止配准过程。我们对带有专家标注地标物的吸气末到呼气末肺 CT 扫描对的注册实验表明，新方法比基于采样的最新技术更快、更准确，特别是对于具有大变形的图像的注册。
