Publication Details




Fidelity and quality improvement of curvilinear image meshing on medical images


Jing Xu and Andrey Chernikov.


Published in VMASC 2016 Capstone Conference, April, 2016




Mesh generation is a useful tool for obtaining discrete descriptors of medical objects represented by images. Different from the conventional meshes with all straight- sided elements, the curvilinear meshes match curved shapes of medical objects that are ubiquitous in nature very well. However, the fidelity (accuracy of the representation) of the mesh boundaries and the quality (measured by Jacobians) of the mesh elements could be deteriorated when transforming straight-sided meshes to curvilinear meshes. In this work we present a technique that allows for the automatic construction of high-order curvilinear meshes with C1 or C2 smooth boundaries. By carefully designing the linear mesh generator, the fidelity is improved compared to the corresponding linear mesh. The paper also provides a technique as a post-processing step that corrects all the invalid elements and improves the mesh quality as measured by their Jacobians. The technique is illustrated with examples and data analysis.




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