Summary
We developed a multi-modality DICOM image dataset that can be used to evaluate the performance of automated de-identification pipelines and protocols. Previously de-identified radiology cases (426) were selected from the Cancer Imaging Archive (TCIA) to use as a validation dataset. The set includes CT, MRI, PET, and radiograph images of most body parts and from various imaging system vendors. The DICOM Standard Security and System Profile was used to create the validation image dataset along with audit logs from TCIA curation of the images. Synthetic PHI/PII and standardized patient IDs were added to DICOM tags in the validation image dataset to mimic non-de-identified images. The validation test dataset and associated de-identified test dataset for 5% of 426 subjects are being released with this publication. This paper describes the validation image dataset creation process, location of associated tables and datasets, and guides for using the dataset. We believe this is the first multi-modality image validation dataset available to the public for use in testing automated image de-identification algorithms.Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.
- Continue with any names from additional submitting sites if collection consists of more that one.
Data Access
Data Type | Download all or Query/Filter |
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Images, (DICOM, XX.X GB) CR, CT, DX, MG, MR, PT | (Download requires the NBIA Data Retriever) |
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Detailed Description
Image Statistics | |
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Modalities | CR, CT, DX, MG, MR, PT |
Number of Patients | 17 |
Number of Studies | 17 |
Number of Series | 20 |
Number of Images | 1823 |
Images Size (GB) |
Citations & Data Usage Policy
Data Citation
Rutherford, M., Mun, S.K., Levine, B., Bennett, W.C., Smith, K., Farmer, P., Jarosz, J., Wagner, U., Farahani, K., Prior, F. (2020). Data from MIDI. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/s17z-r072 (draft, not active).
Publication Citation
We ask on the proposal form if they have ONE traditional publication they'd like users to cite.
Acknowledgement
Only if they ask for special acknowledgments like funding sources, grant numbers, etc in their proposal.
TCIA Citation
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7
Other Publications Using This Data
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Version 1 (Current): Updated yyyy/mm/dd
Data Type | Download all or Query/Filter |
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Images (DICOM, xx.x GB) | (Requires NBIA Data Retriever.) |
Buttons are not populated until collection is released.