Background and objective Fusion of the preoperative computed tomography angiography and intraoperative X-ray angiography images can considerably enhance the visual perception of physicians during percutaneous coronary interventions. This technique can provide 3D information of the arteries and reduce the uncertainty of 2D guidance images. For this purpose, 3D/2D vascular registration with high accuracy and robustness is crucial for performing accurate surgery.

Methods In this study, we propose an iterative closest graph matching (ICGM) method that utilizes an alternative iteration framework including correspondence and transformation phases. A coarse-to-fine matching approach based on redundant graph matching is proposed for the correspondence phase. The transformation phase involves rigid and non-rigid transformations, in which rigid transformation is calculated using a closed-form solution, and non-rigid transformation is achieved using a statistical shape model established from a synthetic deformation dataset.

Results The proposed method is evaluated and compared with nine state-of-the-art methods on simulated data and clinical datasets. Experiments demonstrate that our method is insensitive to the pose of data and robust to noise and deformation. Moreover, it outperforms other methods in terms of registering real data.

Conclusions Given its high capture range, the proposed method can register 3D vessels without prior initialization in clinical practice.

背景和目的术前计算机断层扫描血管造影和术中X射线血管造影图像的融合可以显着增强经皮冠状动脉介入治疗期间医师的视觉感知。该技术可以提供动脉的3D信息并减少2D引导图像的不确定性。为此，具有高精度和鲁棒性的3D / 2D血管定位对于执行精确的手术至关重要。

方法在本研究中，我们提出了一种迭代最接近图匹配（ICGM）方法，该方法利用了包括对应和转换阶段的替代迭代框架。针对通信阶段，提出了一种基于冗余图匹配的粗到精匹配方法。转换阶段涉及刚性和非刚性转换，其中使用闭式解计算刚性转换，并使用从合成变形数据集建立的统计形状模型实现非刚性转换。

结果对拟议的方法进行了评估，并与模拟数据和临床数据集上的九种最新方法进行了比较。实验表明，我们的方法对数据的姿势不敏感，并且对噪声和变形具有鲁棒性。此外，就注册实际数据而言，它优于其他方法。

结论鉴于其捕获范围高，该方法无需事先在临床实践中进行初始化即可注册3D血管。