dcmqi-guide
  • Introduction
  • Quick Start
  • Frequently Asked Questions (FAQ)
  • Tutorials
  • Use cases
    • Multi-structure segmentation of the brain
    • Segmentations and measurements from prostate MRI
  • User guide
    • Installation
      • Binary packages
      • Docker images
      • Build from source
      • 3D Slicer extension
    • General principles
    • Coding schemes
      • DICOM-defined coding schemes
      • Searching for codes outside DICOM
      • "Private" coding schemes
    • Command line tools usage
      • Segmentations
        • itkimage2segimage
        • segimage2itkimage
      • Measurements
        • tid1500writer
        • tid1500reader
      • Parametric maps
        • itkimage2paramap
        • paramap2itkimage
  • Developer guide
    • Update Appveyor build dependencies
    • Github release generation
    • Add new attribute to the schema
  • Troubleshooting
  • Limitations
  • Open source credits
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  • About
  • License
  • Tutorials
  • Support
  • Acknowledgments
  • References
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Introduction

NextQuick Start

Last updated 4 years ago

About

This is user guide for the (DICOM for Quantitative Imaging) library.

With dcmqi you can:

  • Convert certain types of results into standardized DICOM form. This can help you with

    • sharing data in archives like

    • interoperating with PACS and commercial tools

    • supporting data queries to both image data and analysis results

    • standardizing data semantics

    • making your data self-described and better prepared for new uses

  • Convert DICOM data into a commonly used research file formats like JSON and NIfTI.

  • Integrate DICOM concepts into your analysis workflows so that intermediate results are encoded in a standardized manner, making it easy to share your data.

License

dcmqi is distributed under .

Tutorials

Check out our !

Support

You can communicate you feedback, feature requests, comments or problem reports using any of the methods below:

  • post a question to [dcmqi google

Acknowledgments

To acknowledge dcmqi in an academic paper, please cite

References

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Herz C, Fillion-Robin J-C, Onken M, Riesmeier J, Lasso A, Pinter C, Fichtinger G, Pieper S, Clunie D, Kikinis R, Fedorov A. dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM. Cancer Research. 2017;77(21):e87–e90 .

If you like dcmqi, please give the . This is an easy way to show thanks and it can help us qualify for useful services that are only open to widely recognized open projects.

This work is supported primarily by the National Institutes of Health, National Cancer Institute, , grant (U24 CA180918, PIs Kikinis and Fedorov). We also acknowledge support of the following grants: (P41 EB015902, PI Kikinis) and (P41 EB015898, PI Tempany).

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

Herz C, Fillion-Robin J-C, Onken M, Riesmeier J, Lasso A, Pinter C, Fichtinger G, Pieper S, Clunie D, Kikinis R, Fedorov A. dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM. Cancer Research. 2017;77(21):e87–e90 .

dcmqi
quantitative image analysis
TCIA
3-clause BSD license
introductory tutorial
https://groups.google.com/forum/#!forum/dcmqi
submit issue
dcmqi user manual
Andrey Fedorov
http://cancerres.aacrjournals.org/content/77/21/e87
dcmqi repository
a star on github
Informatics Technology for Cancer Research (ITCR) program
Quantitative Image Informatics for Cancer Research (QIICR)
Neuroimage Analysis Center (NAC)
National Center for Image Guided Therapy (NCIGT)
https://doi.org/10.7717/peerj.2057
http://cancerres.aacrjournals.org/content/77/21/e87