An effective registration framework between preoperative 3D computed tomography and intraoperative 2D x-ray images is crucial in image-guided therapy. In this paper, a novel 2D/3D hierarchical registration framework via principal-directional Fourier transform operator (HRF-PDFTO) is proposed. First, a PDFTO was established to obtain the in-plane translation and rotation invariance. Then, an initial free template-matching approach based on PDFTO was utilized to avoid initial value assignment and expand the capture range of registration. Finally, the hierarchical registration framework, HRF-PDFTO, was proposed to reduce the dimensions of the registration search space from n ⁶ to n ². The experimental results demonstrated that the proposed HRF-PDFTO has good performance with an accuracy of 0.72 mm, and a single registration time of 16 s, which improves the registration efficiency by ten times. Consequently, the HRF-PDFTO can meet the accuracy and efficiency requirements of 2D/3D registration in related clinical applications.

术前 3D 计算机断层扫描和术中 2D X 射线图像之间的有效配准框架对于图像引导治疗至关重要。在本文中，提出了一种通过主向傅立叶变换算子（HRF-PDFTO）的新型 2D/3D 分层配准框架。首先，建立PDFTO以获得平面内平移和旋转不变性。然后，利用基于PDFTO的初始自由模板匹配方法来避免初始值分配并扩大配准的捕获范围。最后，提出了分层注册框架 HRF-PDFTO，将注册搜索空间的维度从n ^{6 减少}到n ². 实验结果表明，所提出的HRF-PDFTO具有良好的性能，精度为0.72 mm，单次配准时间为16 s，配准效率提高了10倍。因此，HRF-PDFTO 可以满足相关临床应用中 2D/3D 配准的准确性和效率要求。