Difference between revisions of "Documentation/Nightly/Modules/EncodeSEG"

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Acknowledgments:
 
Acknowledgments:
 
This work is done as part of the [http://imaging.cancer.gov/programsandresources/specializedinitiatives/qin Quantitative Imaging Network (QIN)] initiative of the National Cancer Institute, and is funded by the National Institutes of Health, National Cancer Institute through the grants U24 CA180918 (PIs Kikinis & Fedorov) and U01 CA151261 (PI Fiona Fennessy).<br>
 
This work is done as part of the [http://imaging.cancer.gov/programsandresources/specializedinitiatives/qin Quantitative Imaging Network (QIN)] initiative of the National Cancer Institute, and is funded by the National Institutes of Health, National Cancer Institute through the grants U24 CA180918 (PIs Kikinis & Fedorov) and U01 CA151261 (PI Fiona Fennessy).<br>
Author: Andrey Fedorov ({{collaborator|name|spl}}), Nicole Aucoin ({{collaborator|name|spl}}), Steve Pieper ({{collaborator|name|spl}})<br>
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Author: Andrey Fedorov ({{collaborator|name|spl}}), Steve Pieper ({{collaborator|name|spl}})<br>
 
Contact: Andrey Fedorov, fedorov at bwh dot harvard dot edu<br>
 
Contact: Andrey Fedorov, fedorov at bwh dot harvard dot edu<br>
 
License: [http://www.slicer.org/pages/LicenseText Slicer License]
 
License: [http://www.slicer.org/pages/LicenseText Slicer License]

Revision as of 14:13, 4 January 2016

Home < Documentation < Nightly < Modules < EncodeSEG

For the stable Slicer documentation, visit the 4.10 page.

Introduction and Acknowledgements

Extension: Reporting
Acknowledgments: This work is done as part of the Quantitative Imaging Network (QIN) initiative of the National Cancer Institute, and is funded by the National Institutes of Health, National Cancer Institute through the grants U24 CA180918 (PIs Kikinis & Fedorov) and U01 CA151261 (PI Fiona Fennessy).
Author: Andrey Fedorov (SPL), Steve Pieper (SPL)
Contact: Andrey Fedorov, fedorov at bwh dot harvard dot edu
License: Slicer License

Surgical Planning Laboratory (SPL)  
Isomics, Inc.  
National Alliance for Medical Image Computing (NA-MIC)  
Quantitative Image Informatics for Cancer Research  

Module Description

This module can be used to convert image segmentations saved as raster maps in one of the research formats (i.e., NRRD, NIfTI, MHD) into DICOM Segmentation image object.

Use Cases

See (Fedorov et al. 2015) for details on the PET/CT quantitative analysis use case.

Tutorials

None at this time ... stay tuned!

Parameters:





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     * ': 
     
       ** ': 
       
        *** ': 
       
     
   
 


List of parameters generated transforming this XML file using this XSL file. To update the URL of the XML file, edit this page.


Similar Modules

References

[1] Fedorov A, Clunie D, Ulrich E, Bauer C, Wahle A, Brown B, Onken M, Riesmeier J, Pieper S, Kikinis R, Buatti J, Beichel RR. (2015) DICOM for quantitative imaging biomarker development: A standards based approach to sharing of clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ PrePrints 3:e1921 https://doi.org/10.7287/peerj.preprints.1541v1

Information for Developers