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Home < Documentation < 4.8 < Extensions < DCMQI

For the latest Slicer documentation, visit the 4.10 page.

Introduction and Acknowledgements

Extension: dcmqi
Acknowledgments: This work was supported by the Quantitative Image Informatics for Cancer Research (QIICR) project via the NIH-National Cancer Institute Grant U24 CA180918.
Author: Andrey Fedorov (SPL)
Contributor1: Christian Herz (SPL)
Contributor2: Jean-Christophe Fillion-Robin (Kitware)
Contact: Andrey Fedorov, <email></email>

Quantitative Image Informatics for Cancer Research  
Surgical Planning Laboratory (SPL)  
Kitware, Inc.  

Extension Description


This extension contains the DICOM for Quantitative Imaging (dcmqi) library that provides tools and API for conversions of the quantitative image analysis results (segmentations, measurements, parametric maps) into DICOM format and back.

Use Cases


Usage overview and documentation for the dcmqi library are available at

Panels and their use

The dcmqi extension doesn't provide a GUI, it's intended to be used at the library level by other modules.

Similar Extensions


  • Quantitative Image Informatics for Cancer Research (QIICR)
  • Herz C, Fillion-Robin JC, Onken M, Riesmeier J, Lasso A, Pinter C, Fichtinger G, Pieper S, Clunie D, Kikinis R, Fedorov A. (2017) dcmqi: an open source library for standardized communication of quantitative image analysis results using DICOM. Cancer Research (in press) [PDF]
  • 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

Information for Developers