Documentation/Nightly/Modules/BodyCentricCubicMesh

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Introduction and Acknowledgements

Extension: ImageToMesh (I2M) Conversion Acknowledgments: This work was partially supported by NIH R44 OD018334-03A, grant CCF-1139864 and by the Richard T.Cheng Endowment. Author: Fotis Drakopoulos Contributors: Fotis Drakopoulos (CRTC), Yixun Liu (CRTC), Andrey Fedorov (CRTC), Nikos Chrisochoides (CRTC) Contact: Nikos Chrisochoides, <email>npchris@gmail.com</email> Website: https://crtc.cs.odu.edu/joomla/ License: BSD

Center for Real-time Computing

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

Brain BCC mesh

Nidus BCC mesh

Ventricles BCC mesh

Brain BCC mesh cross-section

Nidus BCC mesh cross-section

Ventricles BCC mesh cross-section

Tutorials

N/A

Panels and their use

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). 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). Input/Output: Labeled Image: The input labeled image. Output Mesh: The output tetrahedral mesh in vtk file format. (default: outputMesh.vtk)

User Interface

Similar Modules

• Documentation/Nightly/Modules/MeshCompression

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.