TY - JOUR
T1 - dcmqi
T2 - An open source library for standardized communication of quantitative image analysis results using DICOM
AU - Herz, Christian
AU - Fillion-Robin, Jean Christophe
AU - Onken, Michael
AU - Riesmeier, Jorg
AU - Lasso, Andras
AU - Pinter, Csaba
AU - Fichtinger, Gabor
AU - Pieper, Steve
AU - Clunie, David
AU - Kikinis, Ron
AU - Fedorov, Andriy
PY - 2017/11/1
Y1 - 2017/11/1
N2 - 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 in the GitHub repository at https://github.com/qiicr/dcmqi.
AB - 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 in the GitHub repository at https://github.com/qiicr/dcmqi.
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U2 - 10.1158/0008-5472.CAN-17-0336
DO - 10.1158/0008-5472.CAN-17-0336
M3 - Article
C2 - 29092948
AN - SCOPUS:85033433885
SN - 0008-5472
VL - 77
SP - e87-e90
JO - Cancer Research
JF - Cancer Research
IS - 21
ER -