2016 Summer Project Week/dcmqi

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  Projects List

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

• Work on the web application for populating SEG metadata
• Add testing and integrate refactoring of the DICOM SEG converter
  • Discuss options for hosting test data: Midas, git-lfs [1], ...
• Work on DICOM SR TID1500 converter
• Explore integration with MITK, MevisLab and Slicer Segmentation Editor

Progress and Next Steps

• Implemented web application for populating SEG metadata: http://qiicr.org/dcmqi
• Parametric maps:
  • Created metadata file which describes required information in order to create DICOM parametric maps
  • Started extending dcmqi API for converting itk to DICOM parametric map and vice versa
• Experimental addition of Brainlab segmentation objects [2]
• Next Steps:
  • Finish implementation of dcmqi API, testing and (extending) web application for populating parametric maps metadata
  • Creation of demo for RSNA 2016 that will include SEG and SR support

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