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A meshing pipeline for biomedical computing

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Abstract

Biomedical computing applications often require a computational pipeline that integrates data from experimental measurements or from image acquisition into a modeling and visualization environment. The latter process often involves segmentation, mesh generation, and numerical simulations. An important requirement of the numerical approximation and visualization methods is the need to create a discrete decomposition of the model geometry into a ‘mesh’. The meshes produced are used both as input for computational simulation and as the geometric basis for many of the resulting visualizations. Historically, the generation of these meshes has been a significant bottleneck in efforts to efficiently create complex, three-dimensional biomedical models. In this paper, we will outline a pipeline for more efficiently generating meshes suitable for biomedical simulations. Because of the wide array of geometries and phenomena encountered in biomedical computing, this pipeline, SCIRun, will incorporate a flexible suite of tools that will offer some generality to mesh generation of biomedical models. We will discuss several tools that have been successfully used in past problems and how these tools have been incorporated into SCIRun. We will demonstrate mesh generation for example problems along with methods for verifying the quality of the meshes generated. Finally, we will discuss ongoing and future efforts to bring all of these tools into a common environment to dramatically reduce the difficulty of mesh generation for biomedical simulations.

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Authors and Affiliations

  1. Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA

    Michael Callahan, Martin J. Cole, Jason F. Shepherd, Jeroen G. Stinstra & Chris R. Johnson

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  1. Michael Callahan
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  2. Martin J. Cole
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  3. Jason F. Shepherd
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  4. Jeroen G. Stinstra
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  5. Chris R. Johnson
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Correspondence to Jason F. Shepherd.

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Callahan, M., Cole, M.J., Shepherd, J.F. et al. A meshing pipeline for biomedical computing. Engineering with Computers 25, 115–130 (2009). https://doi.org/10.1007/s00366-008-0106-1

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