dcmqi: An open source library for standardized communication of quantitative image analysis results using DICOM

Christian Herz, Jean Christophe Fillion-Robin, Michael Onken, Jorg Riesmeier, Andras Lasso, Csaba Pinter, Gabor Fichtinger, Steve Pieper, David Clunie, Ron Kikinis, Andriy Fedorov

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)e87-e90
JournalCancer Research
Volume77
Issue number21
DOIs
StatePublished - Nov 1 2017
Externally publishedYes

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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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. (2017). dcmqi: An open source library for standardized communication of quantitative image analysis results using DICOM. Cancer Research, 77(21), e87-e90. https://doi.org/10.1158/0008-5472.CAN-17-0336