Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Instituted of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China.
Int J Comput Assist Radiol Surg. 2024 Jan;19(1):109-117. doi: 10.1007/s11548-023-02933-y. Epub 2023 Jun 18.
The 3D/2D coronary artery registration technique has been developed for the guidance of the percutaneous coronary intervention. It introduces the absent 3D structural information by fusing the pre-operative computed tomography angiography (CTA) volume with the intra-operative X-ray coronary angiography (XCA) image. To conduct the registration, an accurate matching of the coronary artery structures extracted from the two imaging modalities is an essential step.
In this study, we propose an exhaustive matching algorithm to solve this problem. First, by recognizing the fake bifurcations in the XCA image caused by projection and concatenating the fractured centerline fragments, the original XCA topological structure is restored. Then, the vessel segments in the two imaging modalities are removed orderly, which generates all the potential structures to simulate the imperfect segmentation results. Finally, the CTA and XCA structures are compared pairwise, and the matching result is obtained by searching for the structure pair with the minimum similarity score.
The experiments were conducted based on a clinical dataset collected from 46 patients and comprising of 240 CTA/XCA data pairs. And the results show that the proposed method is very effective, which achieves an accuracy of 0.960 for recognizing the fake bifurcations in the XCA image and an accuracy of 0.896 for matching the CTA/XCA vascular structures.
The proposed exhaustive structure matching algorithm is simple and straightforward without any impractical assumption or time-consuming computations. With this method, the influence of the imperfect segmentations is eliminated and the accurate matching could be achieved efficiently. This lays a good foundation for the subsequent 3D/2D coronary artery registration task.
3D/2D 冠状动脉配准技术已被开发用于经皮冠状动脉介入治疗的指导。它通过融合术前计算机断层血管造影（CTA）体积与术中 X 射线冠状动脉造影（XCA）图像，引入了缺失的 3D 结构信息。为了进行配准，从两种成像方式中提取的冠状动脉结构的精确匹配是一个必要的步骤。
在这项研究中，我们提出了一种穷举匹配算法来解决这个问题。首先，通过识别 XCA 图像中由于投影而产生的假分叉，并将断裂的中心线碎片连接起来，恢复原始的 XCA 拓扑结构。然后，有序地去除两种成像方式中的血管段，生成所有潜在的结构来模拟不完美的分割结果。最后，将 CTA 和 XCA 结构进行两两比较，通过搜索具有最小相似度得分的结构对来获得匹配结果。
实验基于从 46 名患者中收集的临床数据集进行，其中包括 240 对 CTA/XCA 数据对。结果表明，所提出的方法非常有效，在识别 XCA 图像中的假分叉方面的准确率达到 0.960，在匹配 CTA/XCA 血管结构方面的准确率达到 0.896。
所提出的穷举结构匹配算法简单直接，没有任何不切实际的假设或耗时的计算。通过这种方法，可以消除不完美分割的影响，并有效地实现精确匹配。这为后续的 3D/2D 冠状动脉配准任务奠定了良好的基础。
