This is user guide for the dcmqi (DICOM for Quantitative Imaging) library.
dcmqi you can:
- Convert certain types of quantitative image analysis results into standardized DICOM form. This can help you with
- sharing data in archives like TCIA
- interoperating with PACS and commercial tools
- supporting data queries to both image data and analysis results
- standardizing data semantics
- making your data self-described and better prepared for new uses
- Convert DICOM data into a commonly used research file formats like JSON and NIfTI.
- Integrate DICOM concepts into your analysis workflows so that intermediate results are encoded in a standardized manner, making it easy to share your data.
Check out our introductory tutorial!
You can communicate you feedback, feature requests, comments or problem reports using any of the methods below:
This work is supported in part 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).
- 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