Documentation/4.1/Extensions/LesionSegmentation - Revision history

Grundlett: Text replacement - "(.)@(.)<\/email>" to "$1{{@}}$2"

2019-11-27T05:34:05Z

Text replacement - "<email>(.*)@(.*)<\/email>" to "$1{{@}}$2"

UpdateBot: Prepend documentation/versioncheck template. See http://na-mic.org/Mantis/view.php?id=2887

2013-06-14T07:22:08Z

Prepend documentation/versioncheck template. See http://na-mic.org/Mantis/view.php?id=2887

Mscully: Changed to extensions with multiple modules format

2012-06-21T20:05:24Z

Changed to extensions with multiple modules format

Mscully: Initial version

2012-06-21T18:28:47Z

Initial version

New page

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{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
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Extension: [[Documentation/{{documentation/version}}/Extensions/LesionSegmentation|LesionSegmentation]]<br>
Acknowledgments:
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>
Author: Mark Scully ({{collaborator|name|Biomedical Mining}})<br>
Contact: Mark Scully, <email>mark@biomedicalmining.com</email><br>
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{{documentation/{{documentation/version}}/module-section|Module Description}}
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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# Training a new model.

# Segmenting Lesions based on an existing model.


{{documentation/{{documentation/version}}/module-section|Tutorials}}
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
http://frontiersin.org/neuroscience/humanneuroscience/paper/10.3389/fnhum.2010.00027/


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 {{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
 Author: Mark Scully, (Biomedical Mining)<br>
-Contact: Mark Scully, <email>mark@biomedicalmining.com</email><br>
+Contact: Mark Scully, mark{{@}}biomedicalmining.com<br>
 License: [http://www.slicer.org/pages/LicenseText Slicer]

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 {{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
-{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
+Author: Mark Scully, (Biomedical Mining)<br>
 Contact: Mark Scully, <email>mark@biomedicalmining.com</email><br>
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+License: [http://www.slicer.org/pages/LicenseText Slicer]
-{{documentation/{{documentation/version}}/module-introduction-logo-gallery
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-{{documentation/{{documentation/version}}/module-section|Module Description}}
+{{documentation/{{documentation/version}}/extension-section|Extension Description}}
-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.
+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}}/module-section|Use Cases}}
+{{documentation/{{documentation/version}}/extension-section|Use Cases}}
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-{{documentation/{{documentation/version}}/module-section|Tutorials}}
+{{documentation/{{documentation/version}}/extension-section|Tutorials}}
 Coming soon!
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-{{documentation/{{documentation/version}}/module-section|Similar Modules}}
+{{documentation/{{documentation/version}}/extension-section|Similar Extensions}}
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-{{documentation/{{documentation/version}}/module-section|References}}
+{{documentation/{{documentation/version}}/extension-section|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/
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-{{documentation/{{documentation/version}}/module-section|Information for Developers}}
+{{documentation/{{documentation/version}}/extension-section|Information for Developers}}
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+{{documentation/{{documentation/version}}/extension-developerinfo}}
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Documentation/4.1/Extensions/LesionSegmentation - Revision history

Grundlett: Text replacement - "(.*)@(.*)<\/email>" to "$1{{@}}$2"

UpdateBot: Prepend documentation/versioncheck template. See http://na-mic.org/Mantis/view.php?id=2887

Mscully: Changed to extensions with multiple modules format

Mscully: Initial version

Grundlett: Text replacement - "(.)@(.)<\/email>" to "$1{{@}}$2"