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Pattern Recognition
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Extracting curve skeletons for vascular structures is vital for many medical applications. However, most of existing curve skeleton extraction methods are either too complicated or not robust to be applied directly on vascular meshes. In this paper, we present a simple and robust three-step approach for one-dimensional curve skeleton extraction for vascular models. Firstly, the given vascular mesh is iteratively contracted until it is thin enough. Then the contracted mesh is further subdivided. Thereafter our approach proceeds over the point cloud domain yielded by the vertices of the subdivided mesh. Secondly, the joint and branch points of the model are detected. Finally, a skeleton growing procedure is proposed to generate the curve skeleton. Experimental results show that our approach is robust for vascular structures of any topology, e.g. with or without loops or with nearby structures. Additional experiments demonstrate that our approach can be extended to handle other common shapes.