Geodesic
Generation of computational meshes from MRI and CT-scan data
Alban Pagès1 ; Maxime Sermesant2 ; Pascal Frey1
1 CEA/LIST - Laboratoire Jacques Louis Lions
2 King's College London
ESAIM. Proceedings, Tome 14 (2005), pp. 213-223 Cet article a éte moissonné depuis la source EDP Sciences

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There are fields of engineering where accurate and personalised data are required; biomedical applications are one such example. We describe here a general purpose method to create computational meshes based on the analysis and segmentation of raw medical imaging data. The various ingredients are not new: a segmentation method based on deformable contours and a surface and volume mesh adaptation method based on discrete metric specifications; but the challenge that motivated this paper is to put them together in an attempt to design an automatic, easy to use and efficient 3D code.
For non-engineering (like biomedical) applications, the user interface is often a key point. In this project, we put a great deal of emphasis on the automation of the whole procedure, making then possible to envisage large scale simulations with a minimal amount of user interaction. In particular, the user knowledge is required to help segmenting the image (the user is expected to have the know-how of the body anatomy), all meshing steps rely on fully automatic algorithms depending on a few parameters (for the external surface approximation).
One application example is presented and commented, for which the data preparation takes a few hours and results can be obtained overnight on a PC workstation.
DOI : 10.1051/proc:2005016

Alban Pagès 1 ; Maxime Sermesant 2 ; Pascal Frey 1

1 CEA/LIST - Laboratoire Jacques Louis Lions
2 King's College London 
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Alban Pagès; Maxime Sermesant; Pascal Frey. Generation of computational meshes from MRI and CT-scan data. ESAIM. Proceedings, Tome 14 (2005), pp. 213-223. doi: 10.1051/proc:2005016

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