Difference between revisions of "Documentation/4.1/Extensions/LesionSegmentation"

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Author: Mark Scully, (Biomedical Mining)<br>
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Extension: [[Documentation/{{documentation/version}}/Extensions/LesionSegmentation|LesionSegmentation]]<br>
 
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Acknowledgments:
 
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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.<br>
 
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Author: Mark Scully ({{collaborator|name|Biomedical Mining}})<br>
 
 
Contact: Mark Scully, <email>mark@biomedicalmining.com</email><br>
 
Contact: Mark Scully, <email>mark@biomedicalmining.com</email><br>
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This extension contains multiple CLI modules for segmenting white matter lesions in sMRI data.  In order to use these tools your data must include a T1, T2, FLAIR, and brain mask for each subject.  All data must be preprocessed including intra-subject co-registration, AC-PC alignment, bias correction, consistent spacing between sequences, and brain mask creation.  If you are training a new model then expert lesion segmentations (co-registered to the anatomical scans for the relevant subject) are also required.
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LesionSegmentation is a set of open source modules for white matter lesion segmentation in sMRI.  It supports the creation of segmentation models based on a users data and segmentation of subject's lesions using existing models.
  
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*[[Documentation/{{documentation/version}}/Modules/TrainModel|LesionSegmentation->TrainModel]]
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*[[Documentation/{{documentation/version}}/Modules/PredictLesions|LesionSegmentation->PredictLesions]]
  
 
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# Training a new model.
 
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# Segmenting Lesions based on an existing model.
 
  
 
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Coming soon!
 
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* Scully M, Anderson B, Lane T, Gasparovic C, Magnotta V, Sibbitt W, Roldan C, Kikinis R and Bockholt HJ (2010) An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus. Front. Hum. Neurosci. doi:10.3389/fnhum.2010.00027
 
* Scully M, Anderson B, Lane T, Gasparovic C, Magnotta V, Sibbitt W, Roldan C, Kikinis R and Bockholt HJ (2010) An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus. Front. Hum. Neurosci. doi:10.3389/fnhum.2010.00027
 
http://frontiersin.org/neuroscience/humanneuroscience/paper/10.3389/fnhum.2010.00027/
 
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Revision as of 20:05, 21 June 2012

Home < Documentation < 4.1 < Extensions < LesionSegmentation


Introduction and Acknowledgements

Author: Mark Scully, (Biomedical Mining)
Contact: Mark Scully, <email>mark@biomedicalmining.com</email>
License: Slicer


Extension Description

LesionSegmentation is a set of open source modules for white matter lesion segmentation in sMRI. It supports the creation of segmentation models based on a users data and segmentation of subject's lesions using existing models.

Modules

Use Cases

Tutorials

Coming soon!

Similar Extensions

N/A

References

  • Scully M, Anderson B, Lane T, Gasparovic C, Magnotta V, Sibbitt W, Roldan C, Kikinis R and Bockholt HJ (2010) An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus. Front. Hum. Neurosci. doi:10.3389/fnhum.2010.00027

http://frontiersin.org/neuroscience/humanneuroscience/paper/10.3389/fnhum.2010.00027/

Information for Developers

Work in progress
 Section under construction.
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