Exacta ISSN: Universidade Nove de Julho Brasil

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Exacta ISSN: 1678-5428 exacta@uninove.br Universidade Nove de Julho Brasil Massayoshi Sakamoto, Mauro; Cardoso, José Roberto; Marcio Machado, José An automated tetrahedral mesh generator for computer simulation in Odontology based on the Delaunay's algorithm Exacta, vol. 6, núm. 2, julio-diciembre, 2008, pp. 237-243 Universidade Nove de Julho São Paulo, Brasil Available in: http://www.redalyc.org/articulo.oa?id=81011748007 How to cite Complete issue More information about this article Journal's homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative

Artigos An automated tetrahedral mesh generator for computer simulation in Odontology based on the Delaunay s algorithm Mauro Massayoshi Sakamoto Doutorado em Engenharia Elétrica USP; Pesquisador do LMAG PEA EP-USP; São Paulo SP [Brasil] mauro@pea.usp.br José Roberto Cardoso Livre docência em Engenharia Elétrica EP-USP; Professor titular da EP-USP; São Paulo SP [Brasil] cardoso@pea.usp.br José Marcio Machado Doutorado em Engenharia Elétrica pela USP Professor adjunto do DCCE IBILCE UNESP São Paulo SP [Brasil] jmarcio@ibilce.unesp.br In this work, a software package based on the Delaunay s algorithm is described. The main feature of this package is the capability in applying discretization in geometric domains of teeth taking into account their complex inner structures and the materials with different hardness. Usually, the mesh generators reported in literature treat molars and other teeth by using simplified geometric models, or even considering the teeth as homogeneous structures. Key words: Finite Element Method. Tetrahedral mesh generation. Three-dimensional Delaunay algorithm. Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008. 237

1 Introduction The Finite Element Method (FEM), although possessing a very high potential for applications in computer simulation and analysis of biological tissues and structures, for its operation, it is necessary a good (realistic) discretization of the related geometric domains in finite element meshes. Whenever anisotropic or non-homogeneous properties are present, the different regions of the problem must be conveniently identified and discretized into finite elements with consistency. Flaws in the mesh generation, also known as degeneracies, such as overlapping (superposition of elements) and sliver tetrahedra (flat elements of near-zero volume), should be absent. Besides, it is desired that the mesh generation algorithm itself should be robust, and require few manual interactions from the user during the computer simulation. Although the improvement of three-dimensional mesh generation methods still remains a research topic for the FEM applications community, a remarkable degree of maturation and experience was already reached for some approaches (LIN et al., 1999; KRŠEK; KRUPA, 2003; CLEMENT et al., 2004). Apart from this, Delaunay s algorithm and its variations are efficient for regular and irregular solid modeling, such as the geometry of the tooth anatomy (HERMELINE, 1982; MARRETO; MACHADO, 1998). This study will describe the implementation of a C++ program, developed with help of object oriented programming concepts, which implements and applies Delaunay s algorithm for the generation of 3D meshes in teeth structures (SAKAMOTO, 2001; MARRETO; MACHADO, 1998). A special care was taken for the realistic description of internal structures, and meshes with more than 7000 tetrahedra were generated in the test cases. In the next sections, the tooth embedding and image processing is addressed, a short review of the Delaunay s algorithm is presented, and software descriptions and test examples are shown to demonstrate the efficiency code. 2 Tooth embedding and image processing In order to apply the Delaunay s algorithm in computer simulations in odontology, a set of points describing the tooth surface model must be obtained. For discretization, the tooth is included in resin and this inclusion is sliced in a number of parallel cuts, defining cross sections of the tooth. The different boundary regions (enamel, dentine, pulp) are scanned to generate sets of points. An inferior molar for instance may be sliced into 12 different cuts with 1 mm of thickness. The union of these point sets reproduces the three-dimensional tooth geometry, and B-spline interpolations are used if it is necessary, to improve some contour interfaces. This is in fact the classical and easiest approach for geometry generation, and is mentioned for example in Lin et al. (1999). Figure 1 shows a cloud of points for an inferior molar slice and the original boundary regions; Figure 2 shows the dental boundaries detected by the slices, and Figure 3 shows the entire cloud of measured points for all slices. It should be remarked that the Delaunay s algorithm requires only the clouds of points as input, and breakings of prescribed boundaries (if they are present) may be corrected after the discretization by comparison and remeshing. 3 The three-dimensional Delaunay algorithm Most of the implementations of Delaunay algorithm, a given three-dimensional domain is cha- 238 Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008.

Artigos Figure 1: The original slice and measure points of the tooth Figure 3: The entire cloud of measured points for all slices Figure 2: Dental boundaries detected of the slices racterized as a discrete set of points, which will be inserted recursively one at a time as the original mesh grows. The most common implementation of this algorithm is due to Watson (1981), and contains essentially four steps: An initial mesh of tetrahedra is formed by taking a combination of the 8 vertices of a box which encloses the volume to be discretized into tetrahedra. The box dimensions are selected in such a way that all points in the volume are perfectly included by the box and far from its boundaries; In a typical working stage of Watson technique, a new point from the volume is inserted, and a test is made to select those circumspheres of the existing tetrahedra which will contain this new point. The selected tetrahedral are then compared and their common faces are removed. The mesh is updated by forming new tetrahedra with the inserted point and the remaining faces; These new tetrahedra in step 2 are combined with those in which the associated circumspheres do not contain the inserted point; Steps 2 and 3 are repeated recursively for all points forming the volume. Once the mesh is finished, all tetrahedral containing vertices from the enclosing box are deleted. The basic process may be outlined as follows in Table 1: Some degeneration may occur in this technique such as: overlapping (tetrahedra superposition), sliver tetrahedra (flat elements of near-zero volume) and failures in the inclusion test (SUGIHARA; INAGAKI, 1995). This is mainly due to round-off errors and points placed exactly Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008. 239

Table 1: Delaunay tetrahedralization algorithms FOR i=1 TO number of points FOR j=1 TO number of tetrahedra Compute the circumsphere Cj of the tetrahedron T j IF C j contains the point i THEN Add T j to the list of faces, Add T j to the list of candidates for deletion, Mark T j for deletion from the list of tetrahedra in the mesh. END; END; Eliminates the tetrahedra marked for deletion. Eliminate all common faces in the list of faces. Form new tetrahedra with point i and the remaining faces according to the algorithm. Add these tetrahedra to the list of tetrahedra. END. Source: Watson, 1981. on the boundaries, but cures and diagnostics were already extensively discussed in several articles (CAVENDISH; FIELD; FREY, 1985; PRIEST, 1991; SHEWCHUK, 1996; 1997) and properly treated in this study. In relation to treatment of the degeneracies, an alternative developed by the authors to reduce the degenerated Delaunay tetrahedralization is to verify the determinant associated with the new tetrahedra. In this case, no determinant should be null, otherwise the matrix is singular and a new combination should be used. This can be established through a small arbitrary perturbation in the input vertices, or in addition of new points in specific places. This implementation was executed in two phases: The programs for mathematical model, The functions for graphics visualization. In the phase 1, a version of the algorithm was developed using the C++ oriented objects programming language for to of Windows and Linux environment. In the phase 2, the graphic library resources of Mathematics package (version 5.0) were adapted for graphic visualization (WOLFRAM, 1991). In the next section, it is described the validation tests, performances and some implemented cures for mesh degeneration. 4 Validatiom Tests Due to the peculiar features of geometry and internal structures of a tooth, some degenerate tetrahedra may occur in the discretization. According to our experiments, the most frequent degeneracies to appear were: The rupture of internal boundaries between regions; The generation of overlapping elements; Sliver tetrahedral. The rupture of boundaries (shown in Figure 4) is corrected by the local insertion of a new point, close to the medium point in the affected subdomain boundary. Non-convex subdomains may also disturb the mesh quality, but in this case a simple cure is performed by deleting the tetrahedra in the convex subdomain. Figure 5 shows this kind of correction. As already mentioned in the previous section, sliver tetrahedra and overlappings can be miminized by generation of non-singular matrix. The remaining overlappings are corrected by slight disturbances of the original point coordinates, followed by insertion, discretization and subsequent reset to the original coordinate values. However, overlappings were very rare since the domain to discretize is not a regular solid (KANAGANATHAN, 1991). The software has detection routines which minimize these degenerations and allow few interventions from the user during the meshing process. In order to validate the resulting mesh quality, the implementation was tested for a set of discretization points of an inferior molar geometry. Two kinds of meshes were generated: a tooth without 240 Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008.

Artigos inner structures, only enamel, and a tooth with internal structure, i.e., enamel, dentine and pulp. Figure 6 shows a meshed slice from the tooth, and Figure 7 is the entire mesh including all inserted points (without internal structure). The enamel, dentine and pulp meshed structures are shown in Figures 8, 9 and 10 respectively. Figure 11 is a cut in the three-dimensional structure, showing the different meshed regions and their boundaries. It is clear that interfaces between regions and the entire geometry were preserved by the final mesh. The Table 2 shows the number of elements generated in the mesh of the tooth surface model (only enamel) and the final mesh taking into account the different tissues (enamel, dentine and pulp). Figure 5: Disturb of the mesh in non-convex subdomains and the correction 5 Concluding Remarks In the Finite Element Method (FEM) analysis, solid modeling and discretization are the most time demanding steps, requiring a great amount of user intervention. In this article, a software tool for the meshing of irregular solids was described, which is capable of realistic meshing dental structures. Figure 6: Meshed slice from the inferior molar Figure 4: The rupture of boundaries Figure 7: Mesh of the tooth without internal structure (only enamel tissue) Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008. 241

Figure 8: The enamel meshed structure Figure 11: Cut in the three-dimensional structure Table 2: Number of elements for an inferior molar Materials with different hardness Tetrahedra number Only enamel tissue 3251 Enamel, dentine and pulp tissues 7094 Figure 9: The dentine meshed structure Results shown were plenty satisfactory, allowing the possibility of accurate stress simulations and other applications in Dentistry. Future works intend to apply three-dimensional Delaunay refinement algorithms that offer a guarantee on some measure of shape, such as bounded aspect ratio, non-obtuse elements, and tetrahedra with no small angles, except the small angles inherent in the input geometry. Besides, dental biomechanics, determination of stress and strain levels can be investigated. Acknowledgements Figure 10: The pulp meshed structure The authors would like to thank the Faculdade de Odontologia (FO) from Araçatuba for their assistance with the supplied material. 242 Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008.

Artigos References CAVENDISH, J. C.; FIELD, D. A.; FREY, W. H. An approach to automatic three-dimensional finite element mesh generation. International Journal for Numerical Methods in Engineering, USA, v. 21, p. 329-347, 1985. CLEMENT, R.; SCHNEIDER, J.; BRAMBS, H. J.; WUNDERLICH, A.; SANDER, F. G. Quasi-automatic 3D finite element model generation for individual single-rooted teeth and periodontal ligament. Computer Methods and Programs in Biomedicine, Ireland, v. 73, (2), p. 135-144, 2004. HERMELINE, F. Triangulation automatique dún polyèdre en dimension n. R.A.I.R.O. Analyse Numérique/Numerical Analysis, Paris, v. 16, n. 3, p. 211-242, May 1982. KANAGANATHAN, S.; GOLDSTEIN, N. B. Comparison of four-point adding algorithms for Delaunay-type three-dimensional mesh generators, IEEE Transactions on Magnetics, v. 27, n. 3, p. 3444-3451, 1991. KRŠEK, P.; KRUPA, P., Human tissue geometrical modelling. In: Applied Simulation Modeling. Calgary, CA: IASTED, 2003. p. 372-362. LIN, C. L.; CHANG, C. H.; CHENG, C. S.; LEE, H. E. Automatic finite element mesh generation for maxillary second premolar. Computer Methods and Programs in Biomedicine, Ireland, v. 59, p. 187-195, 1999. MARRETO, C. A. R.; MACHADO, J. M. A compact library for automatic generation of tetrahedral meshes using the mathematica system. Proc. of 8th International IGTE Symposium on Numerical Field Calculation in Electrical Engineering & European TEAM Workshop, Austria 1998, p. 116-120. PRIEST, D. M. Algorithms for arbitrary precision floating point arithmetic. Proc. 10th Symposium on Computer Arithmetic, California: IEEE Computer Society Press, 1991. p. 132-143. SAKAMOTO, M. M. Implementação de um gerador tridimensional de malhas de elementos finitos com aplicações à simulação computacional em odontologia. 2001. Dissertação (Mestrado)- Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista, São José do Rio Preto, 2001. SHEWCHUK, J. R. Robust adaptive floating-point geometric predicates. Proc. of 12th Annual Symposium on Computational Geometry, Pennsylvania, 1996, p. 141-150. SHEWCHUK, J. R. Delaunay refinement mesh generation. 1997. PhD. Thesis. School of Computer Science, Carnegie Mellon University, Pennsylvania, 1997. SUGIHARA, K.; INAGAKI, H. Why is the 3D Delaunay triangulation difficult to construct? Information Processing Letters, Ireland, v. 54, p. 275-280, 1995. WATSON, D. F. Computing the n-dimensional Delaunay tessellation with application to Voronoi polytopes, Comput. J., London, England, v. 24, p. 167-172, 1981. WOLFRAM, S. Mathematica: A system for doing mathematics by computer. 2 nd ed. Redwood City, Canada: Addison-Wesley, 1991. Recebido em 13 ago. 2008 / aprovado em 11 dez. 2008 Para referenciar este texto SAKAMOTO, M. M.; CARDOSO, J. R.; MACHADO, J. M. An automated tetrahedral mesh generator for computer simulation in Odontology based on the Delaunay s algorithm. Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008. Exacta, São Paulo, v. 6, n. 2, p. 237-243, jul./dez. 2008. 243