Difference between revisions of "Modules:SpineSegmentation-Documentation-3.6"

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__NOTOC__
 
__NOTOC__
 
===Module Name===
 
===Module Name===
SpineSegmentation module for Slicer 3.6
+
SpineSegmentation module for Slicer 3.6 (available through Slicer extension manager)
  
 
{|
 
{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
+
|[[Image:SpineSegmentation_Slicer3.6_documentation00.png|thumb|300px|A sample data set is available on http://nitrc.org. Download both .mhd and .zraw files.]]
|[[Image:screenshotBlank.png|thumb|280px|Output]]
+
|[[Image:SpineSegmentation_Slicer3.6_documentation02.png|thumb|300px|The SpineSegmentation module is available through the Slicer extension module manager.]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
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|[[Image:SpineSegmentation_Slicer3.6_documentation09.png|thumb|300px|After 3 minutes, the segmentation results appear: a label map (blue) and a 3D model (3D view).]]
 
|}
 
|}
  
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===Authors, Collaborators & Contact===
 
===Authors, Collaborators & Contact===
* Sylvain Jaume: MIT & logo, if desired
+
* Sylvain Jaume: MIT CSAIL
* Contact: Sylvain Jaume, sylvain at csail.mit.edu
+
* Contact: sylvain at csail.mit.edu
 +
{|
 +
|[[Image:MIT_NAMIC_Logo.png|thumb|200px|MIT & NA-MIC]]
 +
|}
  
 
===Module Description===
 
===Module Description===
Image segmentation of the spinal cord and the cerebro-spinal fluid in T2-weighted MRI images. The SpineSegmentation module implements a model-based pattern recognition algorithm for fully automated segmentation.
+
Image segmentation of the spinal cord and the cerebro-spinal fluid in T2-weighted MRI images. The SpineSegmentation module builds on Pattern Recognition theory to provide for a fully automated segmentation. The module first defines a shape model of the spinal cord modeling both the inner volume and the outer volume. Then the segmentation algorithm uses this model to explored the image space and find the best match given the field on intensities in the image. The advantage of this method relies on its unsupervised property: no need for any parameter setting or any initialization.
  
 
== Usage ==
 
== Usage ==
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===Use Cases, Examples===
 
===Use Cases, Examples===
  
This module is especially appropriate for these use cases:
+
This module is especially appropriate for this use case:
  
* Use Case 1:
+
* Automated segmentation of MRI of the spine is critical during minimally invasive intervention when frequent acquisitions of intra-operative images prevents the manual segmentation of the image by an expert. The SpineSegmentation module provides a solution to reduce the burden on the radiologist.
* Use Case 2:
 
  
 
Examples of the module in use:
 
Examples of the module in use:
  
* Example 1
+
* Image-guided surgery for the treatment of disk herniation
* Example 2
+
 
 +
===Tutorial===
 +
Below are the step-by-step instructions to load, process and save some sample data (see link above).
 +
 
 +
* Step 0/9. Download Sample Data
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation00.png|thumb|600px|0. download sample data]]
 +
|}
 +
The sample data sets MRI_Spine.mhd and MRI_Spine.zraw are available at the link below. You will need to create a username on http://nitrc.org. Then log onto nitrc.org and click on the link below. Right-click on MRI_Spine.mhd and MRI_Spine.zraw to copy those files to your local directory.
 +
http://www.nitrc.org/plugins/scmsvn/viewcvs.php/Slicer3/Modules/SpineSegmentation/TestingData/?root=sylvainproject
 +
 
 +
* Step 1/9. Load the sample data
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation01.png|thumb|600px|1. load sample data]]
 +
|}
 +
 
 +
* Step 2/9. Select the SpineSegmentation module.
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation02.png|thumb|600px|2. select SpineSegmentation module]]
 +
|}
 +
 
 +
* Step 3/9. Select the input image.
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation03.png|thumb|600px|3. select input image]]
 +
|}
  
===Tutorials===
+
* Step 4/9. Create a Slicer node for the output image.
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation04.png|thumb|600px|4. create image node]]
 +
|}
  
Links to tutorials explaining how to use this module:
+
* Step 5/9. Create a Slicer node for the output model.
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation05.png|thumb|600px|5. create model node]]
 +
|}
  
* Tutorial 1
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* Step 6/9. Apply the segmentation algorithm.
** Data Set 1
+
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation06.png|thumb|600px|6. apply algorithm]]
 +
|}
  
===Quick Tour of Features and Use===
+
* Step 7/9. Review segmentation result.
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation07.png|thumb|600px|7. review result]]
 +
|}
 +
The sliders on the top of each 2D view allows for reviewing the segmentation result overlaid on the input image.
  
A list panels in the interface, their features, what they mean, and how to use them. For instance:
+
* Step 8/9. Save result image and model.
 +
{|
 +
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation08.png|thumb|600px|8. save results]]
 +
|}
 +
The output image and the 3D model can be saved using the Slicer user interface.
  
 +
* Step 9/9. Find contact information for help and paper reference.
 
{|
 
{|
 
|
 
|
 +
|[[Image:SpineSegmentation_Slicer3.6_documentation09.png|thumb|600px|9. help information]]
 +
|}
 +
 +
===Quick Tour of Features and Use===
 
* '''Input panel:'''
 
* '''Input panel:'''
** '''First input'''
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** '''Image input:''' select the input image
** '''Second input'''
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** '''Image output:''' create Slicer node for output image
* '''Parameters panel:'''
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** '''Model output:''' create Slicer node for output model
** '''First parameter'''
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* '''Command panel:'''
** '''Second parameter'''
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** '''Default:''' reset input and output nodes to blank values
* '''Output panel:'''
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** '''Cancel:''' cancel the execution of the algorithm
** '''First output'''
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** '''Apply:''' apply the segmentation algorithm (takes approx. 3 min)
** '''Second output'''
 
* '''Viewing panel:'''
 
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
 
|}
 
  
 
== Development ==
 
== Development ==
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===Notes from the Developer(s)===
 
===Notes from the Developer(s)===
  
Algorithms used, library classes depended upon, use cases, etc.
+
Reports of new use cases are welcome (email: sylvain at csail.mit.edu). If time permits, we will tune the algorithm for your data sets.
  
 
===Dependencies===
 
===Dependencies===
  
Other modules or packages that are required for this module's use.
+
Linking to Slicer 3.6 is sufficient. This module requires the typical packages bundled with Slicer.
  
 
===Tests===
 
===Tests===
  
On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:
+
Tests are automatically generated using CTest to verify that the module is working on all platforms supported by Slicer.
  
* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
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* SpineSegmentation's [http://www.nitrc.org/plugins/scmsvn/viewcvs.php/Slicer3/Modules/SpineSegmentation/CMakeLists.txt?annotate=151&root=sylvainproject CMakeLists.txt]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]
+
* Slicer's [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard]
  
 
===Known bugs===
 
===Known bugs===
  
Links to known bugs in the Slicer3 bug tracker
+
No bugs have been found yet. If you find a bug, please first email the Slicer mailing list to verify that this is a bug due to SpineSegmentation. Once you have received an answer, follow the link below to add a bug report:
 
 
* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]
 
  
 +
* [http://www.na-mic.org/Bug/view.php? Slicer bug tracker]
  
 
===Usability issues===
 
===Usability issues===
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===Source code & documentation===
 
===Source code & documentation===
  
Links to the module's source code:
+
Module source code (revision 151):
  
Source code:
+
*[http://www.nitrc.org/plugins/scmsvn/viewcvs.php/Slicer3/Modules/SpineSegmentation/SpineSegmentation.cxx?annotate=151&root=sylvainproject SpineSegmentation.cxx]  
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]  
+
*[http://www.nitrc.org/plugins/scmsvn/viewcvs.php/Slicer3/Modules/SpineSegmentation/SpineSegmentation.xml?annotate=151&root=sylvainproject SpineSegmentation.xml]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]
 
 
   
 
   
Doxygen documentation:
+
Doxygen generated documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]
+
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html Slicer Doxygen]
  
 
== More Information ==  
 
== More Information ==  
  
 
===Acknowledgment===
 
===Acknowledgment===
Include funding and other support here.
+
This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (PI: Ron Kikinis).
  
 
===References===
 
===References===
Publications related to this module go here. Links to pdfs would be useful.
+
[http://people.csail.mit.edu/sylvain/Sylvain_Jaume_HBM_poster_2010.pdf Stochastic Neurography], S. Jaume, M. Loepprich, E.J. Schmidt, R. Kikinis, 16th Annual Meeting of the Organization for Human Brain Mapping (HBM 2010), Barcelona, Spain, June 6-10, 2010.

Latest revision as of 13:37, 16 June 2010

Home < Modules:SpineSegmentation-Documentation-3.6

Return to Slicer 3.6 Documentation

Gallery of New Features


Module Name

SpineSegmentation module for Slicer 3.6 (available through Slicer extension manager)

A sample data set is available on http://nitrc.org. Download both .mhd and .zraw files.
The SpineSegmentation module is available through the Slicer extension module manager.
After 3 minutes, the segmentation results appear: a label map (blue) and a 3D model (3D view).

General Information

Module Type & Category

Type: Interactive or CLI

Category: Segmentation

Authors, Collaborators & Contact

  • Sylvain Jaume: MIT CSAIL
  • Contact: sylvain at csail.mit.edu
MIT & NA-MIC

Module Description

Image segmentation of the spinal cord and the cerebro-spinal fluid in T2-weighted MRI images. The SpineSegmentation module builds on Pattern Recognition theory to provide for a fully automated segmentation. The module first defines a shape model of the spinal cord modeling both the inner volume and the outer volume. Then the segmentation algorithm uses this model to explored the image space and find the best match given the field on intensities in the image. The advantage of this method relies on its unsupervised property: no need for any parameter setting or any initialization.

Usage

Use Cases, Examples

This module is especially appropriate for this use case:

  • Automated segmentation of MRI of the spine is critical during minimally invasive intervention when frequent acquisitions of intra-operative images prevents the manual segmentation of the image by an expert. The SpineSegmentation module provides a solution to reduce the burden on the radiologist.

Examples of the module in use:

  • Image-guided surgery for the treatment of disk herniation

Tutorial

Below are the step-by-step instructions to load, process and save some sample data (see link above).

  • Step 0/9. Download Sample Data
0. download sample data

The sample data sets MRI_Spine.mhd and MRI_Spine.zraw are available at the link below. You will need to create a username on http://nitrc.org. Then log onto nitrc.org and click on the link below. Right-click on MRI_Spine.mhd and MRI_Spine.zraw to copy those files to your local directory.

http://www.nitrc.org/plugins/scmsvn/viewcvs.php/Slicer3/Modules/SpineSegmentation/TestingData/?root=sylvainproject
  • Step 1/9. Load the sample data
1. load sample data
  • Step 2/9. Select the SpineSegmentation module.
2. select SpineSegmentation module
  • Step 3/9. Select the input image.
3. select input image
  • Step 4/9. Create a Slicer node for the output image.
4. create image node
  • Step 5/9. Create a Slicer node for the output model.
5. create model node
  • Step 6/9. Apply the segmentation algorithm.
6. apply algorithm
  • Step 7/9. Review segmentation result.
7. review result

The sliders on the top of each 2D view allows for reviewing the segmentation result overlaid on the input image.

  • Step 8/9. Save result image and model.
8. save results

The output image and the 3D model can be saved using the Slicer user interface.

  • Step 9/9. Find contact information for help and paper reference.
9. help information

Quick Tour of Features and Use

  • Input panel:
    • Image input: select the input image
    • Image output: create Slicer node for output image
    • Model output: create Slicer node for output model
  • Command panel:
    • Default: reset input and output nodes to blank values
    • Cancel: cancel the execution of the algorithm
    • Apply: apply the segmentation algorithm (takes approx. 3 min)

Development

Notes from the Developer(s)

Reports of new use cases are welcome (email: sylvain at csail.mit.edu). If time permits, we will tune the algorithm for your data sets.

Dependencies

Linking to Slicer 3.6 is sufficient. This module requires the typical packages bundled with Slicer.

Tests

Tests are automatically generated using CTest to verify that the module is working on all platforms supported by Slicer.

Known bugs

No bugs have been found yet. If you find a bug, please first email the Slicer mailing list to verify that this is a bug due to SpineSegmentation. Once you have received an answer, follow the link below to add a bug report:

Usability issues

Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.

Source code & documentation

Module source code (revision 151):

Doxygen generated documentation:

More Information

Acknowledgment

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (PI: Ron Kikinis).

References

Stochastic Neurography, S. Jaume, M. Loepprich, E.J. Schmidt, R. Kikinis, 16th Annual Meeting of the Organization for Human Brain Mapping (HBM 2010), Barcelona, Spain, June 6-10, 2010.