A Graph Theoretic Exploration of Coronary Vascular Trees
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The aim of this study was to automate the generation of small coronary vascular networks from large point clouds that represent the coronary arterial network. Smaller networks that can be generated in a predictable manner can be used to assess the impact of network morphometry on, for example, blood flow in hemodynamic simulations. We develop a set of algorithms for generating coronary vascular networks from large point clouds. These algorithms sort the point cloud, simplify its network structure without information loss, and produce subgraphs based on given, physiologically meaningful parameters. The data were originally collected from optical fluorescence cryomicrotome images and processed before their use here.
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