Multi-tissue mesh generation for brain images ∗ Yixun Liu 1,2 , Panagiotis Foteinos 1,2 , Andrey Chernikov 2 , and Nikos Chrisochoides 2 1 Department of Computer Science, The College of William and Mary, {enjoywm, pfot}@cs.wm.edu 2 Department of Computer Science, Old Dominion University, {andrey.n.chernikov, npchris}@gmail.com Summary. 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 reso- lution 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. 1 Introduction Multi-tissue mesh generation of medical images is a necessary procedure for building a heterogeneous biomechanical model, which has numerous applica- tions such as physical model-based non-rigid registration, segmentation and surgery simulation. However, there is little literature addressing this issue so far. Several groups [1, 2, 3] presented multi-tissue mesh generation methods based on Delaunay refinement. However, elements with small dihedral angles (a.k.a, slivers) are likely to occur in Delaunay meshes, because elements are removed only when their radius-edge ratio is large; their dihedral angle quality is completely ignored. Meyer et al. [3] showed at least 0.6% slivers occurred in their experiments on frog data. Boltcheva et al. [1] and Pons et al. [2] employed sliver exudation postprocessing technique [4] to remove slivers and showed very good quality mesh (minimal dihedral angle is larger than 4 degrees). ∗ This work is supported in part by NSF grants: CCF-0916526, CCF-0833081, and CSI-719929 and by the John Simon Guggenheim Foundation.