Frequently asked questions
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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 to learn about the requirements for such submissions!
IDC works closely with 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 .
IDC data is stored in the cloud buckets, and you can search and 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 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 . US-based researchers can also access free cloud-based computing resources via .
IDC pilot release took place in Fall 2020, followed by the production release in September 2021.
Please cite the latest paper from the IDC team. Please also make sure you acknowledge the specific data collections you used in your analysis.
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
partial
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:
We host most of the public collections from . We also host HTAN and other pathology images not hosted by TCIA. You can review the complete, up-to-date list of .
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).
The main website for the Cancer Research Data Commons (CRDC) is
Clinical data that was shared by the submitters is available for a number of imaging collections in IDC. Please see 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 provides the API to locate such related datasets.
from our Getting Started tutorial series explains how to use - a python package that aims to simplify access to IDC data
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 to search using some of the attributes that are not available through the portal. You can also to include additional attributes.