Image-based meshing: Difference between revisions

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'''Image-based meshing''' is the automated process of creating computer models for [[computational fluid dynamics]] (CFD) and [[Finite element method|finite element analysis]] (FEA) from 3D image data (such as [[magnetic resonance imaging]] (MRI), [[computed tomography]] (CT) or [[microtomography]]). Although a wide range of [[mesh generation]] techniques are currently available, these were usually developed to generate models from [[computer-aided design]] (CAD), and have therefore have difficulties meshing from 3D imaging data.

==Mesh generation from 3D imaging data==

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===CAD-based approach===

The majority of approaches used to date still follow the traditional CAD route by using an intermediary step of surface reconstruction which is then followed by a traditional CAD-based meshing algorithm.<ref>Viceconti et al, 1998. TRI2SOLID: an application of reverse engineering methods to the creation of CAD models of bone segments. Computer Methods and Programs in Biomedicine, 56, 211–220.</ref>. CAD-based approaches use the scan data to define the surface of the ___domain and then create elements within this defined boundary. Although reasonably robust algorithms are now available, these techniques are often time consuming, and virtually intractable for the complex topologies typical of image data. They also do not easily allow for more than one ___domain to be meshed, as multiple surfaces are often non-conforming with gaps or overlaps at interfaces where one or more structures meet.<ref>Young et al, 2008. An efficient approach to converting 3D image data into highly accurate computational models. ''Philosophical Transactions of the Royal Society A'', 366, 3155&ndash;3173.</ref>.

===Image-based approach===

This approach is the more direct way as it combines the geometric detection and mesh creation stages in one process which offers a more robust and accurate result than meshing from surface data. The most commonly applied meshing procedures are the voxelVoxel conversion technique providing meshes with brick elements <ref>Fyhrie et al, 1993. The probability distribution of trabecular level strains for vertebral cancellous bone. Transactions of the 39th Annual Meeting of the Orthopaedic Research Society, San Francisco.</ref> and the [[Marching cubes]] algorithm providing meshes with tetrahedral elements <ref>Frey et al, 1994. Fully automatic mesh generation for 3-D domains based upon voxel sets. ''International Journal of Methods in Engineering'', 37, 2735–2753.</ref> have been proposed.

A newer enhanced volumetric marching cubesAnother approach generates 3D hexahedraltetrahedral or tetrahedral elements throughout the volume of the ___domain, thus creating the mesh directly with conforming multipart surfaces. In the case of modeling complex topologies with possibly hundreds of disconnected domains, this approach is remarkably straightforward, robust, accurate and efficient<ref>Young et al, 2008. An efficient approach to converting 3D image data into highly accurate computational models. ''Philosophical Transactions of the Royal Society A'', 366, 3155&ndash;3173.</ref>.

==Generating a model==

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An extensive range of [[image processing]] tools can be used to generate highly accurate models based on data from 3D imaging modalities, e.g. MRI, CT, MicroCT (XMT), and Ultrasound. Features of particular interest include:

* [[Segmentation (image processing)|Segmentation tools]] (e.g. thresholding, floodfill, level set methods, etc.)

* [[Smoothing|Filters and smoothing tools]] (e.g. volume- and topology-preserving smoothing and noise reduction/artefact removing).

===Volume and surface mesh generation===

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* Mapping functions to apply material properties based on signal strength (e.g. [[Young's modulus]] to [[Hounsfield scale]])

* Smoothing of meshes (e.g. topological preservation of data to ensure preservation of connectivity, and volume neutral smoothing to prevent shrinkage of convex hulls)

* Export to FEA and CFD codes for analysis (e.g. nodesnode sets, shell elements, material properties, contact surfaces, boundary layers, inlets/outlets)

==Typical use==

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* [[Paleontology]] and [[Morphology (biology)|functional morphology]]

* [[Reverse engineering]]

* [[Soil science]] and [[petrology]]

* [[Petrophysics]]

==See also==

*[[Image segmentation]]

==References==

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==External links==

* [https://www.computing-objects.com/ Computing-Objects] commercial C++ libraries for mesh generation & FEM computation

* Simpleware[[ScanIP]] commercial image-based meshing software: [http://www.simpleware.com www.simpleware.com]

* Mimics 3D image-based engineering software for FEA and CFD on anatomical data: [http://www.materialise.com/mimics Mimics website] {{Webarchive|url=https://web.archive.org/web/20110212150457/http://www.materialise.com/mimics |date=2011-02-12 }}

* Google group on image-based modelling: [http://groups.google.co.uk/group/image-based-modelling]

* [[Avizo (software)|Avizo Software]]'s 3D image-based meshing tools for CFD and FEA

* iso2mesh: a free 3D surface and volumetric mesh generator for matlab/octave [https://iso2mesh.sourceforge.net/]

[[Category:Numerical differential equations]]

* [http://www.ctcms.nist.gov/oof/ OOF3D], object oriented finite element analysis from the [[NIST]]

[[Category:Numerical analysis]]

* [https://www.volumegraphics.com/en/products/vgstudio-max/add-on-modules-for-simulation.html VGSTUDIO MAX], Commercial CT analysis software for industry. They offer an add-on module for FEM meshing.

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[[Category:NumericalMesh analysisgeneration]]

[[Category:Computer graphics algorithms]]

[[Category:3D computer graphics]]