IEEE Trans Med Imaging. 2014 May;33(5):1023-34. doi: 10.1109/TMI.2014.2300117.
2D/3D registration of patient vasculature from preinterventional computed tomography angiography (CTA) to interventional X-ray angiography is of interest to improve guidance in percutaneous coronary interventions. In this paper we present a novel feature based 2D/3D registration framework, that is based on probabilistic point correspondences, and show its usefulness on aligning 3D coronary artery centerlines derived from CTA images with their 2D projection derived from interventional X-ray angiography. The registration framework is an extension of the Gaussian mixture model (GMM) based point-set registration to the 2D/3D setting, with a modified distance metric. We also propose a way to incorporate orientation in the registration, and show its added value for artery registration on patient datasets as well as in simulation experiments. The oriented GMM registration achieved a median accuracy of 1.06 mm, with a convergence rate of 81% for nonrigid vessel centerline registration on 12 patient datasets, using a statistical shape model. The method thereby outperformed the iterative closest point algorithm, the GMM registration without orientation, and two recently published methods on 2D/3D coronary artery registration.
从术前计算机断层血管造影 (CTA) 到介入性 X 射线血管造影对患者血管的 2D/3D 配准引起了人们的兴趣，以改善经皮冠状动脉介入治疗的指导。本文提出了一种新颖的基于概率点对应关系的基于特征的 2D/3D 配准框架，并展示了其在将源自 CTA 图像的 3D 冠状动脉中心线与源自介入性 X 射线血管造影的 2D 投影对齐方面的有用性。配准框架是基于高斯混合模型 (GMM) 的点集配准到 2D/3D 配准的扩展，具有修改后的距离度量。我们还提出了一种在配准中包含方向的方法，并展示了其在患者数据集上以及在模拟实验中进行动脉配准的附加价值。定向 GMM 配准使用统计形状模型对 12 个患者数据集上的非刚性血管中心线进行非刚性配准，其平均准确性为 1.06 毫米，收敛率为 81%。该方法优于迭代最近点算法、无定向 GMM 配准以及最近发表的两种 2D/3D 冠状动脉配准方法。
