Check out the downloading-data documentation page!
Note that currently IDC prioritizes submissions from NCI-funded driving projects and data from special selected projects.
- If you would like to submit images, it will be your responsibility to de-identify them first, documenting the de-identification process and submitting that documentation for the review by IDC stakeholders.
- We welcome submissions of image-derived data (expert annotations, AI-generated segmentations) for the images already in IDC, see IDC Zenodo community Curation policy to learn about the requirements for such submissions!
IDC works closely with The Cancer Imaging Archive (TCIA) and mirrors TCIA public collections. If you submit your DICOM data to TCIA and your data is released as a public collection, it will be automatically available in IDC in a following release.
If you are interested in making your data available within IDC, please contact us by sending email to [email protected].
IDC data is stored in the cloud buckets, and you can search and download data from IDC for free and without login.
If you would like to use the cloud for analysis of the data, we recommend you start with the free tier of Google Colab to get free access to a cloud-hosted VM with GPU to experiment with analysis workflows for IDC data. If you are an NIH-funded researcher, you may be eligible for a free allocation via NIH Cloud Lab. US-based researchers can also access free cloud-based computing resources via ACCESS program allocations.
IDC pilot release took place in Fall 2020, followed by the production release in September 2021.
We host most of the public collections from The Cancer Imaging Archive (TCIA). We also host HTAN and other pathology images not hosted by TCIA. You can review the complete, up-to-date list of collections included in IDC.
Please cite the latest paper from the IDC team. Please also make sure you acknowledge the specific data collections you used in your analysis.
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., Kim, E. & Kikinis, R. National cancer institute imaging data commons: Toward transparency, reproducibility, and scalability in imaging artificial intelligence. Radiographics 43, (2023). https://doi.org/10.1148/rg.230180
IDC and TCIA are partners in providing FAIR data for cancer imaging researchers. While some of the functions between the two resources are similar, there are also key differences. The table below provides a summary of similarities and differences.
| Function | IDC | TCIA |
|---|---|---|
| De-identification | no, IDC can only host data already de-identified | yes |
| Cloud-based data co-located with compute resources | yes | no |
| Conversion of pathology images and image-derived data into DICOM format | yes | no |
| Private data collections | no | yes |
| Public data collections | yes | yes |
| Version control of the data | yes | no |
The main website for the Cancer Research Data Commons (CRDC) is https://datacommons.cancer.gov/
Clinical data that was shared by the submitters is available for a number of imaging collections in IDC. Please see this tutorial on how to search that data and how to link clinical data with imaging metadata!
Many of the imaging collections are also accompanied by the genomics or proteomics data. CRDC Cancer Data Aggregator (CDA) provides the API to locate such related datasets.
IDC Portal gives you access to just a small subset of the metadata accompanying IDC images. If you want to learn more about what is available, you have several options:
- this notebook from our Getting Started tutorial series explains how to use
idc-index- a python package that aims to simplify access to IDC data - this more advanced notebook will help you get started with searching IDC metadata in BigQuery, which gives you access to all of the DICOM metadata extracted from IDC-hosted files
- if you are not comfortable writing queries or coding in pyhon, you can use this DataStudio dashboard to search using some of the attributes that are not available through the portal. You can also extend this dashboard to include additional attributes.