The National Cancer Institute Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data, co-located with analysis and exploration tools. As part of the NCI Cancer Research Data Commons (CRDC), IDC provides researchers with:

• Access to ~100 TB of cancer imaging data, including radiology, brightfield, and fluorescence microscopy images
• Image-derived data such as annotations, segmentations, and quantitative measurements
• Accompanying clinical data
• Cloud-based infrastructure for data exploration and analysis

• Free and open access: No registration or access requests required
• Commercial-friendly licensing: >95% of data covered by CC-BY license
• Cloud-based: Data available from both Google and AWS public buckets
• Standardized data: All images and derived data harmonized into DICOM format

To begin using IDC:

• Check out imaging-data-commons-skill - a plugin for your LLM agent that offers natural language interface to interacting with IDC
• Visit our official website https://portal.imaging.datacommons.cancer.gov/
• Explore our Getting started guide in the IDC Documentation
• Join the IDC User Forum for community support and discussions

Our GitHub organization hosts various repositories to support IDC users:

• IDC-Tutorials: Self-guided notebook tutorials to help you get started with IDC
• idc-index: python package for searching, downloading, and simplifying access to the data in IDC
• SlicerIDCBrowser: 3D Slicer extension providing access to IDC data
• idc-wsi-conversion: PixelMed Toolkit based scripts used in IDC for converting vendor-specific slide microscopy formats into DICOM WSI representation

We are also maintianing a number of repositories containing popular tools that we use in IDC, but which are of general utility:

• highdicom: high-level DICOM abstractions for the Python programming language
• Slim: interoperable web-based DICOM slide microscopy viewer and annotation tool
• dicom-microscopy-viewer: Web-based DICOM slide microscopy viewer library
• dicomweb-client: python client for DICOMweb RESTful services
• libdicom: C library for reading DICOM files
• s5cmd-python-distributions: package that allows you to install s5cmd command line tools with pip
• plastimatch-python-distributions: pip-installable binaries of Plastimatch
• dcmqi-python-distributions: pip-installable binaries of dcmqi

If you need assistance or have questions, please:

• Open a new topic in the IDC User Forum (preferred)
• Send us a message at support at canceridc dot dev

We're excited to support your cancer imaging research with IDC!