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Multi-tissue mesh generation for brain images

Yixun Liu, Panagiotis Foteinos, Andrey Chernikov, and NikosChrisochoides

Proceedings, 19th International Meshing Roundtable, Springer-Verlag, pp.367-384, October 3-6 2010


19th International Meshing Roundtable
Chattanooga, Tennessee, USA.
October 3-6, 2010

Department of Computer Science, The College of William and Mary,
Email: {enjoywm, pfot}
Department of Computer Science, Old Dominion University,
Email: {andrey.n.chernikov, npchris}

We develop a multi-tissue mesh generation method that is suitable for finite element simulation involved in non-rigid registration and surgery simulation of brain images. We focus on the following four critical mesh properties: tissue- dependent resolution, delity to tissue boundaries, smoothness of mesh surfaces, and element quality. Each mesh property can be controlled on a tissue level. This method consists of two steps. First, a coarse multi-tissue mesh with tissue-dependent reso- lution is generated according to a predefined subdivision criterion. Then, a tissue- aware point-based registration method is used to nd an optimal trade-o among fidelity, smoothness, and quality. We evaluated our method on a number of images ranging from MRI, visible human, to brain atlas. The experimental results verify the features of this method.

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