Difference between revisions of "Documentation/Nightly/Modules/QuadEdgeSurfaceMesher"

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*'''Input image''': input segmentation image
 
*'''Label to mesh''': label ID to use for triangulation
 
*'''Decimation constant''': parameter that determines the number of the triangles in the output surface mesh as a proportion of the triangles in the mesh produced by marching cubes.
 
*'''Output triangulated surface''': surface model that to store the result
 
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Latest revision as of 14:02, 4 January 2016

Home < Documentation < Nightly < Modules < QuadEdgeSurfaceMesher


For the latest Slicer documentation, visit the read-the-docs.


Introduction and Acknowledgements

SlicerProstate Logo 1.0 128x128.png

Extension: SlicerProstate
Acknowledgments: This work supported in part the National Institutes of Health, National Cancer Institute through the following grants:

  • Quantitative MRI of prostate cancer as a biomarker and guide for treatment, Quantitative Imaging Network (U01 CA151261, PI Fennessy)
  • Enabling technologies for MRI-guided prostate interventions (R01 CA111288, PI Tempany)
  • The National Center for Image-Guided Therapy (P41 EB015898, PI Tempany)
  • Quantitative Image Informatics for Cancer Research (QIICR) (U24 CA180918, PIs Kikinis and Fedorov).

Authors: Andrey Fedorov (SPL)
Contact: Andrey Fedorov, <email>fedorov@bwh.harvard.edu</email>

License: Slicer License


National Center for Image Guided Therapy (NCIGT)  
Quantitative Image Informatics for Cancer Research  
Surgical Planning Laboratory (SPL)  

Module Description

This module can be used as an alternative to ModelMaker to generate a smooth triangulated surface of a segmented label with improved (in the opinion of the author of this module) control over the number of triangles in the output surface, as well as improved visual appearance of the result. In the example below, the Marching Cubes output has 18750 triangles (blue), ModelMaker with 0.5 smoothing and 0.5 decimation generates 11173 triangles, (red) and the output of QuadEdgeSurfaceMesher (yellow) contains 1606 triangles. The result produced by ModelMaker with decimation setting set to 0.99 (a parameter similar to the decimation constant of the module being presented) produces triangulation that looks too embarrassing to show here.

Visualization of the result of the marching cubes algorithm (blue), ModelMaker output with 0.5 decimation and 0.5 smoothing settings (red) and the QuadEdgeSurfaceMesher module (single parameter DecimationConstant = 0.01) (yellow).
Visualization of the result (wireframe visualization) of the marching cubes algorithm (blue), ModelMaker output with 0.5 decimation and 0.5 smoothing settings (red) and the QuadEdgeSurfaceMesher module (single parameter DecimationConstant = 0.01) (yellow). Note the number, uniformity and quality of the triangles in the yellow trianglulation.

This module was motivated by the need to generate smooth compact surface triangulations for prostate MRI images.

The module operates by applying Marching Cubes algorithm to the input segmentation, and then uses the ITK filters implementing the approach described in [1]. Currently, the module does not support multiple labels.

Use Cases

  • MRI-ultrasound fusion biopsy of the prostate (primary)
  • therapy planning
  • treatment response assessment

Tutorials

None at this time ... stay tuned!


Parameters:

  • IO: Input/output parameters
    • Input image (inputImageName): Segmentation label image
    • Label to mesh (labelId): Label to mesh. By default, segmentation corresponding to label 1 will be meshed.
    • Decimation constant (decimationConst): Number of cells in the output mesh will be the original number of cells times the decimation constant
    • Output triangulated surface (outputMeshName): Surface


List of parameters generated transforming this XML file using this XSL file. To update the URL of the XML file, edit this page.


Similar Modules

ModelMaker

References

[1] Gelas A, Gouaillard A, Megason S (2008) Surface meshes incremental decimation framework. Insight J http://www.insight-journal.org/browse/publication/298

[2] Fedorov A, Khallaghi S, Antonio Sánchez C, Lasso A, Fels S, Tuncali K, Neubauer Sugar E, Kapur T, Zhang C, Wells W, Nguyen PL, Abolmaesumi P, Tempany C. (2015) Open-source image registration for MRI–TRUS fusion-guided prostate interventions. Int J CARS: 1–10. Available: http://link.springer.com/article/10.1007/s11548-015-1180-7.

[3] Fedorov A, Nguyen PL, Tuncali K, Tempany C. (2015). Annotated MRI and ultrasound volume images of the prostate. Zenodo. http://doi.org/10.5281/zenodo.16396

Information for Developers