Abstract
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, fidelity 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 resolution is generated according to a predefined subdivision criterion. Then, a tissue-aware point-based registration method is used to find an optimal trade-off 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.
This work is supported in part by NSF grants: CCF-0916526, CCF-0833081, and CSI-719929 and by the John Simon Guggenheim Foundation.
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Liu, Y., Foteinos, P., Chernikov, A., Chrisochoides, N. (2010). Multi-tissue Mesh Generation for Brain Images. In: Shontz, S. (eds) Proceedings of the 19th International Meshing Roundtable. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15414-0_22
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DOI: https://doi.org/10.1007/978-3-642-15414-0_22
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