Difference between revisions of "Documentation/4.1/Extensions/LesionSegmentation"
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− | + | Author: Mark Scully, (Biomedical Mining)<br> | |
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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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* 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/ | http://frontiersin.org/neuroscience/humanneuroscience/paper/10.3389/fnhum.2010.00027/ | ||
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Latest revision as of 05:34, 27 November 2019
Home < Documentation < 4.1 < Extensions < LesionSegmentation
For the latest Slicer documentation, visit the read-the-docs. |
Introduction and Acknowledgements
Author: Mark Scully, (Biomedical Mining)
Contact: Mark Scully, markbiomedicalmining.com
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
Section under construction. |