Summary
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.
- David Geffen School of Medicine at UCLA - U01CA181156 Stanford University School of Medicine – U01CA187947 and U24CA180927 University of Michigan - U01CA232931 University of Washington – R50CA211270, U01CA148131 University of South Florida - U24CA180927, U01CA200464 Moffitt Cancer Center – U01CA143062, U01CA200464, P30CA076292 UC San Francisco - U01CA225427 BC Cancer Research Centre - NSERC Discovery Grant: RGPIN-2019-06467 Columbia University- U01CA225431 Center for Biomedical Image Computing and Analytics at the University of Pennsylvania - U24CA189523, R01NS042645 Massachusetts General Hospital- U01CA154601, U24CA180927
Data Access
Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.
| Data Type | Download all or Query/Filter |
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| Images (DICOM, XX.X GB) |
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| Supplemental Data (format) |
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Click the Versions tab for more info about data releases.
Detailed Description
Image Statistics | |
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Modalities | DICOM, NIfTI, SEG |
Number of Patients | 32 |
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Number of Series | |
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Add any additional information as needed below. Likely would be something from site.
Citations & Data Usage Policy
Add any special restrictions in here.
These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:
Data Citation
Jaggi, A, Mattonen S. A. , McNitt-Gray M, Napel S. DOI goes here. Create using pubhub with information from Collection Approval form
Acknowledgement
M McNitt-Gray, S Napel, A Jaggi, SA Mattonen , L Hadjiiski, M Muzi, D Goldgof, Y Balagurunathan, LA Pierce , PE Kinahan, EF Jones, A Nguyen, A Virkud, H-P Chan, N Emaminejad, M Wahi-Anwar, M Daly, M Abdalah, H Yang, L Lu, W Lv, A Rahmim, A Gastounioti, S Pati, S Bakas, D Kontos, B Zhao, J Kalpathy-Cramer, K Farahani. Standardization in Quantitative Imaging: A Multi-center Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Datasets. Accepted for publication, Tomography, Feb. 2020.
Akshay Jaggi, Sarah A. Mattonen, Michael McNitt-Gray, Sandy Napel. Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features. Accepted for publication pending minor revisions, Tomography, Feb. 2020.
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
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.
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.) |
| Clinical Data (CSV) | Link |
| Other (format) |
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Added new subjects.