@inproceedings{84891302939,
    abstract = "In a medical context, one of the most used techniques to produce an initial mesh (starting from segmented medical images) is the Marching Cubes (MC) introduced by Lorensen and Cline in [1]. Unfortunately, MC presents several issues in the meshing context. These problems can be summarized in three types: topological (presence of holes), of quality (sharp triangles) and accuracy in the representation of the target domain (the staircase effect). Even though there are several solutions to overcome topological and quality issues, the staircase effect remains as a challenging problem. On the other hand, the Computational Geometry Algorithms Library (CGAL) ,has implemented the Poisson Surface Reconstruction algorithm introduced in ,which is capable of producing accurate and high quality triangulations based on a point set and its normal directions. This paper shows how surface meshes can be produced using both, MC and CGAL. Moreover, starting from the generated quality surface mesh, this work also shows how volume meshes can be produced. Therefore, a complete workflow, starting from segmented medical images to surface and volume meshes, is introduced in this work. In particular, tetrahedral and mixed-element meshing techniques are presented to produce a simulation with the Finite Element Method.",
    year = "2013",
    title = "From segmented medical images to surface and volume meshes, using existing tools and algorithms",
    pages = "436-447",
    journal = "Adaptive Modeling and Simulation 2013 - Proceedings of the 6th International Conference on Adaptive Modeling and Simulation, ADMOS 2013"
}

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