About

dcmqi (DICOM for Quantitative Imaging) is a free, open source library that implements conversion between commonly used imaging research formats and the standard DICOM representation. dcmqi can be used to create DICOM objects for storing voxelized image segmentations, parametric maps, and segmentation-based measurements. dcmqi uses DCMTK classess and libraries that support the individual objects, and uses ITK to support research formats.

Availability

Installation: We provide binary packages of dcmqi for Windows, macOS and Linux. We also provide a Docker image of the library. dcmqi can also be installed as an extension to 3D Slicer using 3D Slicer Extension manager. See installation instructions in the [user guide]](https://qiicr.gitbooks.io/dcmqi-guide) for details.

Documentation: link

Source code: link

Publications

• Herz C, Fillion-Robin J-C, Onken M, et al. dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM. Cancer Res. American Association for Cancer Research; 2017;77(21):e87–e90 link - This is the main publication introducing dcmqi.
• Fedorov A, Clunie D, Ulrich E, et al. 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. 2016;4:e2057 link - This paper discusses the capabilities of DICOM in storing some of the data types produced by common image analysis tasks, and is accompanied by sample datasets

Grants support

• U24 CA180918
• P41 EB015902
• P41 EB015898