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For the complete documentation index, see llms.txt. This page is also available as Markdown.

Welcome!

New: query IDC from your AI assistant in plain conversation — see Using IDC with an AI assistant — or call the REST API (v3) directly.

NCI Imaging Data Commons (IDC) is a cloud-based environment containing publicly available cancer imaging data co-located with analysis and exploration tools. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that provides secure access to a large, comprehensive, and expanding collection of cancer research data.

Highlights

  • >95 TB of data: IDC contains radiology, brightfield (H&E) and fluorescence slide microscopy images, along with image-derived data (annotations, segmentations, quantitative measurements) and accompanying clinical data

  • free: all of the data in IDC is publicly available: no registration, no access requests

  • commercial-friendly: >95% of the data in IDC is covered by the permissive CC-BY license, which allows commercial reuse (small subset of data is covered by the CC-NC license); IDC metadata records the license for each individual DICOM series, so you can check and follow the rules for exactly the data you selected - see Licensing and attribution

  • cloud-based: all of the data in IDC is available from both Google and AWS public buckets: fast and free to download, no out-of-cloud egress fees

  • harmonized: all of the images and image-derived data in IDC is harmonized into standard DICOM representation

Functionality

IDC is as much about data as it is about what you can do with the data! We maintain and actively develop a variety of tools that are designed to help you efficiently navigate, access and analyze IDC data:

  • exploration: start with the IDC Portal to get an idea of the data available

  • visualization: examine images and image-derived annotations and analysis results from the convenience of your browser using integrated OHIF, VolView and Slim open source viewers

  • programmatic access: use idc-index python package to perform search, download and other operations programmatically, or the language-agnostic REST API over plain HTTP

  • AI assistants: give Claude or any other agent access to IDC — with the hosted MCP server or the IDC agent skill — to discover, subset, and download IDC data in plain conversation (see Using IDC with an AI assistant)

  • cohort building: use rich and extensive metadata to build subsets of data programmatically using idc-index or BigQuery SQL

  • download: use your favorite S3 API client or idc-index to efficiently fetch any of the IDC files from our public buckets

  • analysis: conveniently access IDC files and metadata from the tools that are cloud-native, such as Google Colab; fetch IDC data directly into 3D Slicer using SlicerIDCBrowser extension

The overview of IDC is available in this open access publication. If you use IDC, please acknowledge us by citing it!

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., 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 (2023). https://doi.org/10.1148/rg.230180

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