This is user guide for the dcmqi (DICOM for Quantitative Imaging) library.
dcmqi you can:
dcmqi is distributed under 3-clause BSD license.
Check out our introductory tutorial!
You can communicate you feedback, feature requests, comments or problem reports using any of the methods below:
dcmqi in an academic paper, please cite
Herz C, Fillion-Robin JC, 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 (in press)
If you like
dcmqi, please give the dcmqi repository a star on github. 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, Informatics Technology for Cancer Research (ITCR) program, grant Quantitative Image Informatics for Cancer Research (QIICR) (U24 CA180918, PIs Kikinis and Fedorov). We also acknowledge support of the following grants: Neuroimage Analysis Center (NAC) (P41 EB015902, PI Kikinis) and National Center for Image Guided Therapy (NCIGT) (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 https://doi.org/10.7717/peerj.2057
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)