2016 Summer Project Week/dcmqi
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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
- created/extended web app for populating SEG metadata: http://qiicr.org/dcmqi
- Regarding parametric maps:
- Created metadata file which describes required information in order to create DICOM parametric maps
- Extended QIIRC API for converting itk to DICOM parametric map and vv (not complete)
- experimental addition of Brainlab segmentation objects [1]
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