Abstract
3D mesh segmentation is a computer graphics research topic, its main goal is segmenting high resolution mesh into meaningful substructures. However, when applying traditional mesh segmentation algorithm to medical mesh data, it encounters problems such as efficiency and noise sensitivity. This paper proposes a pruned mesh segmentation method for high resolution medical mesh data, we improve the algorithm by proposing an approximately sample seed points method and geodesic distance based clustering algorithm. Experimental results demonstrate that our algorithm could accelerate the mesh segmentation algorithm on high resolution medical mesh data without decreasing accuracy.
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