Philips Healthcare, Cardio/Vascular Innovation, Best, The Netherlands.
Int J Comput Assist Radiol Surg. 2009 Jun;4(4):391-7. doi: 10.1007/s11548-009-0316-z. Epub 2009 May 7.
Robust and accurate automated co-registration of the coronary arteries in 3D CTA and 2D X-ray angiography during percutaneous coronary interventions (PCI), in order to present a fused visualization.
A novel vesselness-based similarity measure was developed, that avoids an explicit segmentation of the X-ray image. A stochastic optimizer searches the optimal registration using the similarity measure.
Both simulated data and clinical data were used to investigate the accuracy and capture range of the proposed method. The experiments show that the proposed method outperforms the iterative closest point method in terms of accuracy (average residual error of 0.42 mm vs. 1.44 mm) and capture range (average 71.1 mm/20.3 degrees vs. 14.1 mm/5.2 degrees ).
The proposed method has proven to be accurate and the capture range is ample for usage in PCI. Especially the absence of an explicit segmentation of the interventionally acquired X-ray images considerably aids the robustness of the method.
在经皮冠状动脉介入治疗（PCI）期间，实现冠状动脉在 3D CTA 和 2D X 射线血管造影中的稳健且精确的自动配准，以呈现融合的可视化效果。
开发了一种新的基于血管性的相似性度量方法，该方法避免了 X 射线图像的显式分割。随机优化器使用相似性度量搜索最佳注册。
使用模拟数据和临床数据来研究所提出方法的准确性和捕获范围。实验表明，与迭代最近点方法相比，该方法在准确性（平均残余误差为 0.42 毫米对 1.44 毫米）和捕获范围（平均 71.1 毫米/20.3 度对 14.1 毫米/5.2 度）方面表现更好。
所提出的方法已被证明是准确的，并且捕获范围足以用于 PCI。特别是干预性获取的 X 射线图像不存在显式分割，这极大地提高了方法的稳健性。
