Difference between revisions of "2016 Summer Project Week/dcmqi"

From NAMIC Wiki
Jump to: navigation, search
(Add workaround for Slicer issue http://www.na-mic.org/Bug/view.php?id=4220)
Line 12: Line 12:
 
* Steve Pieper
 
* Steve Pieper
 
* Caspar Goch (Mon)
 
* Caspar Goch (Mon)
 
==References (why does it mess up formatting if I put this section in the end?!!)==
 
 
<small>Problem identified and reported as Slicer issue [http://www.na-mic.org/Bug/view.php?id=4220 #4220]</small>
 
 
* Fedorov A, Clunie D, Ulrich E, Bauer C, Wahle A, Brown B, Onken M, Riesmeier J, Pieper S, Kikinis R, Buatti J, Beichel RR. (2016) DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ 4:e2057 https://doi.org/10.7717/peerj.2057
 
  
 
==Project Description==
 
==Project Description==
Line 39: Line 33:
 
</div>
 
</div>
 
</div>
 
</div>
 +
<br style="clear:left;">
  
 
==References==
 
==References==
 
* Fedorov A, Clunie D, Ulrich E, Bauer C, Wahle A, Brown B, Onken M, Riesmeier J, Pieper S, Kikinis R, Buatti J, Beichel RR. (2016) DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ 4:e2057 https://doi.org/10.7717/peerj.2057
 
* Fedorov A, Clunie D, Ulrich E, Bauer C, Wahle A, Brown B, Onken M, Riesmeier J, Pieper S, Kikinis R, Buatti J, Beichel RR. (2016) DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ 4:e2057 https://doi.org/10.7717/peerj.2057

Revision as of 16:15, 22 June 2016

Home < 2016 Summer Project Week < dcmqi

Key Investigators

  • Andrey Fedorov
  • Christian Herz
  • Marco Nolden
  • Hans Meine
  • Csaba Pinter
  • Steve Pieper
  • Caspar Goch (Mon)

Project Description

Objective

  • dcmqi (DICOM for Quantitative Imaging) is a library to help with the DICOM data handling and conversion tasks in quantitative image analysis.
  • This week we will work to improve functionality of the library, discuss API with the prospective users, and collect feedback.

Approach, Plan

  • Add testing and integrate refactoring of the DICOM SEG converter
    • discuss options for hosting test data: Midas, git-lfs, ...
  • Work on DICOM SR TID1500 converter
  • Explore integration with MITK, MevisLab and Slicer Segmentation Editor
  • Work on the web application for populating SEG metadata

Progress


References

  • Fedorov A, Clunie D, Ulrich E, Bauer C, Wahle A, Brown B, Onken M, Riesmeier J, Pieper S, Kikinis R, Buatti J, Beichel RR. (2016) DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ 4:e2057 https://doi.org/10.7717/peerj.2057