Difference between revisions of "Documentation/Nightly/Extensions/SkeletalRepresentation"

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'''Acknowledgements:''' This work is part of Slicer Shape Analysis Toolbox ([http://salt.slicer.org/ SlicerSALT]), funded by NIH NIBIB R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects), as well as the [https://www.slicer.org/ Slicer community].<br />
 
'''Acknowledgements:''' This work is part of Slicer Shape Analysis Toolbox ([http://salt.slicer.org/ SlicerSALT]), funded by NIH NIBIB R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects), as well as the [https://www.slicer.org/ Slicer community].<br />
  
'''Author:''' Zhiyuan Liu<br />
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'''Author:''' [http://www.cs.unc.edu/~zhiy/ Zhiyuan Liu]<br />
'''Contributors:''' Pablo Hernandez-Cerdan, Jean-Christophe Fillion-Robin, Beatriz Paniagua, Jared Vicory, Junpyo Hong, Stephen M. Pizer<br />
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'''Contributors:''' Pablo Hernandez-Cerdan, [https://www.kitware.com/jean-christophe-fillion-robin/ Jean-Christophe Fillion-Robin], [https://www.kitware.com/beatriz-paniagua/ Beatriz Paniagua], [https://www.kitware.com/jared-vicory/ Jared Vicory], Junpyo Hong, [http://www.cs.unc.edu/~smp/ Stephen M. Pizer]<br />
 
'''Contact:''' Zhiyuan Liu, zhiy at cs dot unc dot edu
 
'''Contact:''' Zhiyuan Liu, zhiy at cs dot unc dot edu
 +
 
== Extension Description ==
 
== Extension Description ==
This extension is an open source tool to establish, optimize and visualize [http://midag.cs.unc.edu/pubs/papers/xavier_book_2019.pdf skeletal representation] (abbreviated as s-rep) of 3D objects in biomedical images. The main features of this extension include:<br />
+
This extension is an open source tool to initialize, refine and visualize [http://midag.cs.unc.edu/pubs/papers/xavier_book_2019.pdf skeletal representation] (abbreviated as s-rep) of 3D objects in biomedical images. The main features of this extension include:<br />
* Establish an s-rep by mean curvature flow of an object boundary<br />
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* Initialize an s-rep by mean curvature flow of an object boundary<br />
* Refine an s-rep to fit an object boundary
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* Refine an s-rep to fit an object boundary<br />
 +
* Visualize the s-rep
 +
S-reps have a number of advantages in shape analysis of human organs. Some previous research has shown the superiority of using s-reps to perform hypothesis testing, classification and shape distribution analysis.
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<gallery>
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SkeletalRepresentation.png|Icon of the extension
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</gallery>
  
 
== Modules ==
 
== Modules ==
 
* Skeletal Representation Initializer
 
* Skeletal Representation Initializer
* Skeletal Representation Optimizer
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* Skeletal Representation Refiner
 
* Skeletal Representation Visualizer
 
* Skeletal Representation Visualizer
 +
 
== Use Cases ==
 
== Use Cases ==
 
Sample data can be found [https://github.com/KitwareMedical/SlicerSkeletalRepresentation/blob/master/SkeletalRepresentationVisualizer/Testing/test_data/hippo.m3d here].<br />
 
Sample data can be found [https://github.com/KitwareMedical/SlicerSkeletalRepresentation/blob/master/SkeletalRepresentationVisualizer/Testing/test_data/hippo.m3d here].<br />
 
<gallery>
 
<gallery>
Example.jpg|Establish an s-rep
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Hippo_mesh.png|The surface mesh of hippocampus
Example.jpg|Visualize an s-rep
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New_srep.png|Visualize the s-rep of the hippocampus
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Initialize.png|Initialize the s-rep of the hippocampus
 
</gallery>
 
</gallery>
  
 
== Tutorials ==
 
== Tutorials ==
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<gallery>
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Srep_tutorial.png|Tutorial for visualization
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Srep_tutorial.png|Tutorial for initialization
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Srep_tutorial.png|Tutorial for refinement
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</gallery>
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== Similar Extensions ==
 
== Similar Extensions ==
 
NA
 
NA
 
== References ==
 
== References ==
 
* Stephen M. Pizer, Junpyo Hong, Jared Vicory, J. S. Marron, and others, "[http://midag.cs.unc.edu/pubs/papers/xavier_book_2019.pdf Object Shape Representation via Skeletal Models (s-reps) and Statistical Analysis]" in Riemannian Geometric Statistics in Medical Image Analysis, no. (Xavier Pennec, Stefan Sommer, and Tom Fletcher, eds.), 2019.
 
* Stephen M. Pizer, Junpyo Hong, Jared Vicory, J. S. Marron, and others, "[http://midag.cs.unc.edu/pubs/papers/xavier_book_2019.pdf Object Shape Representation via Skeletal Models (s-reps) and Statistical Analysis]" in Riemannian Geometric Statistics in Medical Image Analysis, no. (Xavier Pennec, Stefan Sommer, and Tom Fletcher, eds.), 2019.
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* Source code can be found https://github.com/KitwareMedical/SlicerSkeletalRepresentation

Latest revision as of 01:16, 23 October 2019

Home < Documentation < Nightly < Extensions < SkeletalRepresentation

Introduction and Acknowledgements

Acknowledgements: This work is part of Slicer Shape Analysis Toolbox (SlicerSALT), funded by NIH NIBIB R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects), as well as the Slicer community.

Author: Zhiyuan Liu
Contributors: Pablo Hernandez-Cerdan, Jean-Christophe Fillion-Robin, Beatriz Paniagua, Jared Vicory, Junpyo Hong, Stephen M. Pizer
Contact: Zhiyuan Liu, zhiy at cs dot unc dot edu

Extension Description

This extension is an open source tool to initialize, refine and visualize skeletal representation (abbreviated as s-rep) of 3D objects in biomedical images. The main features of this extension include:

  • Initialize an s-rep by mean curvature flow of an object boundary
  • Refine an s-rep to fit an object boundary
  • Visualize the s-rep

S-reps have a number of advantages in shape analysis of human organs. Some previous research has shown the superiority of using s-reps to perform hypothesis testing, classification and shape distribution analysis.

Modules

  • Skeletal Representation Initializer
  • Skeletal Representation Refiner
  • Skeletal Representation Visualizer

Use Cases

Sample data can be found here.

Tutorials

Similar Extensions

NA

References