A Feature Preserved Mesh Subdivision Framework for Biomedical Mesh

Abstract

As biomedical data in 3D space collected increasingly, there is a pressing need for efficient and accurate applications in the field of bioinformation analysis. For biomedical purpose, mesh subdivision techniques are commonly used to generate adaptive multi-resolution meshes for fast or accurate algorithms. However, current smoothing methods for each subdivision algorithm will moderate edge and vertex features from the original mesh. In this paper, we propose a feature preserved mesh subdivision framework, which generates a visually sensitive and a more precise result compared with commonly used subdivision methods, to preserve edge and vertex geometrical features of biomedical data.