Public studies for your demo
Openly licensed studies from the NCI Imaging Data Commons, ready to load in your viewer.
Data rules
- Use only studies from public datasets with a stated license. Your own, a relative's or a patient's study is not allowed, even if de-identified.
- State the source and license of the demo data in the entry.
- Head studies are accepted only when the dataset already ships them without the possibility of face reconstruction.
- Cite the collection as its license requires. Most are CC BY and require credit.
- An entry with identifiable data is removed as soon as it is noticed.
How to download
Install idc-index and run each study's command in the folder where you want the files.
pip install idc-indexStudies
LIDC-IDRI
CT, SEG, SR · CHEST · 35 MB · CC BY 3.0
- StudyInstanceUID
- 1.3.6.1.4.1.14519.5.2.1.6279.6001.210460865401632134346677582159
- Citation
Armato III, Samuel G., McLennan, G., Bidaut, L., McNitt-Gray, M. F., Meyer, C. R., Reeves, A. P., Zhao, B., Aberle, D. R., Henschke, C. I., Hoffman, E. A., Kazerooni, E. A., MacMahon, H., Van Beek, E. J. R., Yankelevitz, D., Biancardi, A. M., Bland, P. H., Brown, M. S., Engelmann, R. M., Laderach, G. E., … Clarke, L. P. (2015). Data From LIDC-IDRI (Version 4) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX
Fedorov, A., Hancock, M., Clunie, D., Brochhausen, M., Bona, J., Kirby, J., Freymann, J., Aerts, H. J. W. L., Kikinis, R., & Prior, F. (2018). Standardized representation of the TCIA LIDC-IDRI annotations using DICOM (Version 3) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2018.H7UMFURQ
idc download 1.3.6.1.4.1.14519.5.2.1.6279.6001.210460865401632134346677582159NSCLC Radiogenomics
CT, PT, SEG · LUNG · 103 MB · CC BY 3.0, CC BY 4.0
- StudyInstanceUID
- 1.3.6.1.4.1.14519.5.2.1.4334.1501.653360657532172299935692201400
- Citation
Bakr, S., Gevaert, O., Echegaray, S., Ayers, K., Zhou, M., Shafiq, M., Zheng, H., Zhang, W., Leung, A., Kadoch, M., Shrager, J., Quon, A., Rubin, D., Plevritis, S., & Napel, S. (2017). Data for NSCLC Radiogenomics Collection (Version 4) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.7HS46ERV
Van Oss, J., Murugesan, G. K., McCrumb, D., & Soni, R. (2024). Image segmentations produced by BAMF under the AIMI Annotations initiative (Version v2.0.2) [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.8345959
idc download 1.3.6.1.4.1.14519.5.2.1.4334.1501.653360657532172299935692201400UPENN-GBM
MR, SEG · BRAIN · 20 MB · CC BY 4.0
- StudyInstanceUID
- 1.3.6.1.4.1.14519.5.2.1.81896212790030501983260473507558407939
- Citation
Bakas, S., Sako, C., Akbari, H., Bilello, M., Sotiras, A., Shukla, G., Rudie, J. D., Flores Santamaria, N., Fathi Kazerooni, A., Pati, S., Rathore, S., Mamourian, E., Ha, S. M., Parker, W., Doshi, J., Baid, U., Bergman, M., Binder, Z. A., Verma, R., … Davatzikos, C. (2021). Multi-parametric magnetic resonance imaging (mpMRI) scans for de novo Glioblastoma (GBM) patients from the University of Pennsylvania Health System (UPENN-GBM) (Version 2) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.709X-DN49
Van Oss, J., Murugesan, G. K., McCrumb, D., & Soni, R. (2024). Image segmentations produced by BAMF under the AIMI Annotations initiative (Version v2.0.2) [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.8345959
idc download 1.3.6.1.4.1.14519.5.2.1.81896212790030501983260473507558407939Prostate-MRI-US-Biopsy
M3D, MR, SEG · PELVIS · 20 MB · CC BY 4.0
- StudyInstanceUID
- 1.3.6.1.4.1.14519.5.2.1.153613283546503819934885929827859483069
- Citation
Ciausu, C., Clunie, D., & Fedorov, A. (2023). DICOM converted annotations for the Prostate-MRI-US-Biopsy collection [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.10069910
Natarajan, S., Priester, A., Margolis, D., Huang, J., & Marks, L. (2020). Prostate MRI and Ultrasound With Pathology and Coordinates of Tracked Biopsy (Prostate-MRI-US-Biopsy) (Version 2) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2020.A61IOC1A
idc download 1.3.6.1.4.1.14519.5.2.1.153613283546503819934885929827859483069CBIS-DDSM
MG · BREAST · 10 MB · CC BY 3.0
- StudyInstanceUID
- 1.3.6.1.4.1.9590.100.1.2.251229393412385867941848541770264573557
- Citation
Sawyer-Lee, R., Gimenez, F., Hoogi, A., & Rubin, D. (2016). Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) (Version 1) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.7O02S9CY
idc download 1.3.6.1.4.1.9590.100.1.2.251229393412385867941848541770264573557
When you use Imaging Data Commons, also cite
Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W. L., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., et al. (2023). National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence. RadioGraphics, 43(12). https://doi.org/10.1148/rg.230180