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DCMQI: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results using DICOM

1Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
2Harvard Medical School, Harvard University, Boston, MA, USA.
3Kitware Inc., Clifton Park, New York, United States of America
4Open Connections GmbH, Oldenburg, Germany.
5Freelancer, Oldenburg, Germany.
6Laboratory for Percutaneous Surgery, School of Computing, Queen’s University, Kingston, Ontario, Canada.
7Isomics, Inc., Cambridge, MA, USA.
8PixelMed Publishing, LLC, Bangor, PA, USA.
9Department of Computer Science, University of Bremen, Bremen, Germany.
10Fraunhofer MEVIS, Bremen, Germany.
American Association for Cancer Research
Publication Date:
Cancer Research
Volume Number:
Issue Number:
Cancer Res. 2017 Nov 1;77(21):e87-e90.
PubMed ID:
quantitative imaging, DICOM, cancer imaging, imaging informatics, open source
Appears in Collections:
U24 CA180918/CA/NCI NIH HHS/United States
P41 EB015902/EB/NIBIB NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
R01 EB014955/EB/NIBIB NIH HHS/United States
Generated Citation:
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 Res. 2017 Nov 1;77(21):e87-e90. PMID: 29092948. PMCID: PMC5675033.
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Quantitative analysis of clinical image data is an active area of research that holds promise for precision medicine, early assessment of treatment response, and objective characterization of the disease. Interoperability, data sharing, and the ability to mine the resulting data are of increasing importance, given the explosive growth in the number of quantitative analysis methods being proposed. The Digital Imaging and Communications in Medicine (DICOM) standard is widely adopted for image and metadata in radiology. dcmqi (DICOM for Quantitative Imaging) is a free, open source library that implements conversion of the data stored in commonly used research formats into the standard DICOM representation. dcmqi source code is distributed under BSD-style license. It is freely available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer. Installation and usage instructions are provided on Harvard DASH.

Additional Material
1 File (159.383kB)
Herz-CancerResearch2017-fig1.jpg (159.383kB)