Difference between revisions of "Documentation/4.0/Modules/EMSegment Easy"

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This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the [http://www.na-mic.org/ NA-MIC website].<br>
 
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|Image:Logo-isomics.png|Isomics, Inc. <- Replace this logo with yours
 
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This module is designed for users who want to do a quick intensity based image segmentation. The remainder of this sections describes the work flow of the two modes in further detail:
  
 
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MR image segmentation
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=== Step 1: Define Input Channel  ===
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Define the number of input channels as well as the name of each channel and the corresponding scan associated with the channel. If using multiple input channel(scans) which are not aligned with each other then check on the check-box button "Align input scans".
 +
=== Step 2: Define Anatomical Tree  ===
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The user specifies the hierarchical relationship between the anatomical structures. The tree will refine the complex segmentation task into a set of easier segmentation problems. A sub-classes is added to an existing structure by right-clicking on the structure and selecting "Add sub-class". The name, label, and color of a structure are modified by selecting the structure in the tree and then defining these attributes in the panel below.
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=== Step 3: Specify Intensity Distribution ===
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Defining the intensity distribution for each structure of interest through taking samples in the image of interest
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=== Step 4: Edit Node-based Parameters ===
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Users specify the relative to weight of a node in the tree with respect to other structures which are children of the same parent node. The first tab also specifies the weight of the input channels as well as the atlases. The value 'Alpha' specifies the smoothing applied to the structure (via MRFs). The second tab (Stopping Condition) lists the number of iterations associated with the segmentation task. By default, the Bias iteration is set to -1 which means that it is performed each iteration. If the value is greater -1 then the inhomogeneity computation is stopped after n iterations. The third tab specifies printing out intermediate results, which are saved in the working directory specified in the next step
 +
=== Step 5: Define Miscellaneous Parameters ===
 +
This panels lists the general parameters necessary for segmenting images. Users can specify a region of interest to speed up the segmentation algorithm. Pressing the 'Segment' button creates a label map of the anatomical structures.
  
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{|style="width: 100%"
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Once the parameters are specified, the target images are segmented
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using the EM Segmentation algorithm (Pohl et al. TMI 2007). The label map with corresponding statistics is returned after successful completion of the algorithm.  
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* Input panel1:
 
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{{documentation/{{documentation/version}}/module-section|Similar Modules}}
 
{{documentation/{{documentation/version}}/module-section|Similar Modules}}
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Please look at [[ Documentation/4.0#Segmentation | Segmentation]] section
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* Point to other modules that have similar functionality
 
* Point to other modules that have similar functionality
  
 
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{{documentation/{{documentation/version}}/module-section|References}}
 
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Publications related to this module go here. Links to pdfs would be useful.
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* Wells III W.M., Grimson W.E.L., Kikinis R., Jolesz F.A. [http://www.spl.harvard.edu/publications/item/view/847 Adaptive segmentation of MRI data.] IEEE Trans Med Imaging. 1996; 15(4):429-442.
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For extensions: link to the source code repository and additional documentation
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* Pohl K.M., Fisher III J.W., Grimson W.E.L., Kikinis R., Wells III W.M. [http://www.spl.harvard.edu/publications/item/view/58 A Bayesian model for joint segmentation and registration.] Neuroimage. 2006 May 15;31(1):228-39.
 +
 +
*Pohl K, Bouix S, Nakamura M, Rohlfing T, McCarley R, Kikinis R, Grimson W, Shenton M, Wells W. [http://www.slicer.org/pages/Special:PubDB_View?dspaceid=608 A Hierarchical Algorithm for MR Brain Image Parcellation.] IEEE Transactions on Medical Imaging. 2007 Sept;26(9):1201-1212. [[http://people.csail.mit.edu/pohl/publications/journal-citation-bib.html#pohl07_3 bib]]
  
 
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Revision as of 19:51, 23 November 2011

Home < Documentation < 4.0 < Modules < EMSegment Easy


Introduction and Acknowledgements

This work was funded by the ARRA Supplement to the Neuroimage Analysis Center (NAC), funded by the National Institutes of Health. Information on NAC can be obtained from the NAC website.
Author: Kilian Pohl, UPenn
Contributor1: Daniel Haehn, UPENN
Contact: Kilian Pohl, <email>pohl.kilian@gmail.com</email>

University of Pennsylvania  
Surgical Planning Laboratory  


Module Description

This module is designed for users who want to do a quick intensity based image segmentation. The remainder of this sections describes the work flow of the two modes in further detail:

Use Cases

MR image segmentation

Tutorials

N/A

Panels and their use

Step 1: Define Input Channel

Define the number of input channels as well as the name of each channel and the corresponding scan associated with the channel. If using multiple input channel(scans) which are not aligned with each other then check on the check-box button "Align input scans".

Step 2: Define Anatomical Tree

The user specifies the hierarchical relationship between the anatomical structures. The tree will refine the complex segmentation task into a set of easier segmentation problems. A sub-classes is added to an existing structure by right-clicking on the structure and selecting "Add sub-class". The name, label, and color of a structure are modified by selecting the structure in the tree and then defining these attributes in the panel below.

Step 3: Specify Intensity Distribution

Defining the intensity distribution for each structure of interest through taking samples in the image of interest

Step 4: Edit Node-based Parameters

Users specify the relative to weight of a node in the tree with respect to other structures which are children of the same parent node. The first tab also specifies the weight of the input channels as well as the atlases. The value 'Alpha' specifies the smoothing applied to the structure (via MRFs). The second tab (Stopping Condition) lists the number of iterations associated with the segmentation task. By default, the Bias iteration is set to -1 which means that it is performed each iteration. If the value is greater -1 then the inhomogeneity computation is stopped after n iterations. The third tab specifies printing out intermediate results, which are saved in the working directory specified in the next step

Step 5: Define Miscellaneous Parameters

This panels lists the general parameters necessary for segmenting images. Users can specify a region of interest to speed up the segmentation algorithm. Pressing the 'Segment' button creates a label map of the anatomical structures.

Once the parameters are specified, the target images are segmented using the EM Segmentation algorithm (Pohl et al. TMI 2007). The label map with corresponding statistics is returned after successful completion of the algorithm.

Similar Modules

Please look at Segmentation section

  • Point to other modules that have similar functionality

References

Information for Developers

Work in progress
 Section under construction.


Note The section above is generated using the following wiki code: 

{{documentation/{{documentation/version}}/module-section|Information for Developers}}
{{documentation/{{documentation/version}}/module-developerinfo|ModuleTemplate|type=Interactive|category=Example}}

If you are documenting a CLI, the category should be extracted from the corresponding XML description. This could be done automatically using the following wiki template:

{{documentation/{{documentation/version}}/module-category|xmlurl=http://path/to/YOURMODULENAME.xml }}

If your module is available in Slicer repository, the following template could be useful to obtain the corresponding URL: 

{{documentation/{{documentation/version}}/module-cli-xmlurl|{{documentation/modulename}}|SVNREVISION}}

Using this later template, the final syntax would be: 

{{documentation/{{documentation/version}}/module-category|xmlurl={{documentation/{{documentation/version}}/module-cli-xmlurl|{{documentation/modulename}}|SVNREVISION}} }}


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