LSIIT UMR CNRS/UdS, Parc d'Innovation, Illkirch, France.
Comput Med Imaging Graph. 2010 Jul;34(5):377-87. doi: 10.1016/j.compmedimag.2010.01.001. Epub 2010 Feb 12.
In this article, we propose an automatic algorithm for coronary artery segmentation from 3D X-ray data sequences of a cardiac cycle (3D-CT scan, 64 detectors, 10 phases). This method is based on recent mathematical morphology techniques (some of them being extended in this article). It is also guided by anatomical knowledge, using discrete geometric tools to fit on the artery shape independently from any perturbation of the data. The application of the method on a validation dataset (60 images: 20 patients in 3 phases) led to 90% correct (and automatically obtained) segmentations, the 10% remaining cases corresponding to images where the SNR was very low.
在本文中，我们提出了一种从心脏周期的三维 X 射线数据序列（3D-CT 扫描，64 个探测器，10 个相位）中自动分割冠状动脉的算法。该方法基于最近的数学形态学技术（其中一些在本文中进行了扩展）。它还受到解剖学知识的指导，使用离散几何工具来拟合动脉形状，而不受数据任何干扰的影响。该方法在验证数据集（60 张图像：3 个相位中的 20 个患者）上的应用导致了 90%的正确（自动获得）分割，其余 10%的情况对应于 SNR 非常低的图像。
