Difference between revisions of "Documentation/Nightly/Modules/BodyCentricCubicMesh"
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* '''Mesh Generation Parameters:''' | * '''Mesh Generation Parameters:''' | ||
** '''Size:''' Controls the size of the mesh. The smaller the value the larger the mesh. Value should be between [1,20] (default: 8). | ** '''Size:''' Controls the size of the mesh. The smaller the value the larger the mesh. Value should be between [1,20] (default: 8). | ||
− | ** '''Fidelity:''' Controls the subdivision of the elements that belong to more than one image labels. The larger the value the better the conformity of the mesh on the image label | + | ** '''Fidelity:''' Controls the subdivision of the elements that belong to more than one image labels. The larger the value the better the conformity of the mesh on the image label boundaries. Value should be between [0.1,1] (default: 0.8). |
** '''Resample Resolution:''' Controls the image resampling. Suggested value is 0 (no-resampling) for large tissues and 1 or 2 for smaller tissues. Value should be 0 or 1 or 2 (default: 0). | ** '''Resample Resolution:''' Controls the image resampling. Suggested value is 0 (no-resampling) for large tissues and 1 or 2 for smaller tissues. Value should be 0 or 1 or 2 (default: 0). | ||
* '''Input/Output:''' | * '''Input/Output:''' |
Revision as of 02:25, 20 June 2014
Home < Documentation < Nightly < Modules < BodyCentricCubicMesh
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Introduction and Acknowledgements
Extension: Image To Mesh Conversion
Author:Fotis Drakopoulos | |||
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Module Description
The module generates a Body Centric Cubic (BCC) mesh from a labeled image. Initially the generated mesh is homogeneous, that means does not distinguish different tissues. Later the module specifies which tissue each tetrahedron belongs to. Each tissue is capable of automatically adjusting its resolution based on its geometric complexity and the predefined subdivision criterion. The current version of the module supports a single-tissue input labeled image.
Use Cases
Panels and their use
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References
- Fedorov A., Chrisochoides N., Kikinis R., Warfield S, "Tetrahedral mesh generation for medical imaging", The Insight Journal-2005 MICCAI Open-Source Workshop, 2005
- Yixun Liu, Panagiotis Foteinos, Andrey Chernikov and Nikos Chrisochoides, "Mesh Deformation-based Multi-tissue Mesh Generation for Brain Images", Engineering with Computers, Volume 28, pages 305-318, 2012.
Information for Developers
Section under construction. |