Documentation/Nightly/Modules/SEG2NRRD

For the latest Slicer documentation, visit the read-the-docs.

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), Nicole Aucoin (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 DICOM Segmentation image object into NRRD format. Relevant metadata is saved in the .info file.

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:

  ()
 
 
   
     * ': 
     
       ** ': 
       
        *** ': 
       
     
   
 

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

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 [2] DICOM Segmentation IOD. http://dicom.nema.org/medical/dicom/current/output/chtml/part03/sect_A.51.html

Information for Developers

• Source code: https://github.com/QIICR/Reporting/blob/master/SEGSupport/EncodeSEG.cxx