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Fully Automatic Detection and Visualization of Patient Specific Coronary Supply Regions

机译：病人特定冠状动脉供血区域的全自动检测和可视化

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Coronary territory maps, which associate myocardial regions with the corresponding coronary artery that supply them, are a common visualization technique to assist the physician in the diagnosis of coronary artery disease. However, the commonly used visualization is based on the AHA-17-segment model, which is an empirical population based model. Therefore, it does not necessarily cope with the often highly individual coronary anatomy of a specific patient. In this paper we introduce a novel fully automatic approach to compute the patient individual coronary supply regions in CTA datasets. This approach is divided in three consecutive steps. First, the aorta is fully automatically located in the dataset with a combination of a Hough transform and a cylindrical model matching approach. Having the location of the aorta, a segmentation and skeletonization of the coronary tree is triggered. In the next step, the three main branches (LAD, LCX and RCX) are automatically labeled, based on the knowledge of the pose of the aorta and the left ventricle. In the last step the labeled coronary tree is projected on the left ventricular surface, which can afterward be subdivided into the coronary supply regions, based on a Voronoi transform. The resulting supply regions can be either shown in 3D on the epicardiac surface of the left ventricle, or as a subdivision of a polarmap.
机译：将心肌区域与提供心肌区域的相应冠状动脉相关联的冠状动脉区域图是一种常见的可视化技术，可帮助医师诊断冠状动脉疾病。但是，常用的可视化基于AHA-17段模型，该模型是基于经验的种群模型。因此，它不一定能应付特定患者经常高度个体化的冠状动脉解剖。在本文中，我们介绍了一种新颖的全自动方法来计算CTA数据集中患者的各个冠状动脉供应区域。该方法分为三个连续的步骤。首先，结合霍夫变换和圆柱模型匹配方法，将主动脉完全自动定位在数据集中。有了主动脉的位置，就触发了冠状动脉树的分割和骨骼化。下一步，根据对主动脉和左心室的姿势的了解，自动标记三个主要分支（LAD，LCX和RCX）。在最后一步中，将标记的冠状动脉树投影在左心室表面上，然后根据Voronoi变换将其细分为冠状动脉供血区域。产生的供应区域可以在左心室的心外膜表面上以3D形式显示，也可以以极谱图的细分形式显示。

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