NCI Imaging Data Commons (idc-index)

Overview

NCI Imaging Data Commons (IDC) is the largest public collection of cancer imaging data, hosting 175+ DICOM collections (CT, MR, PET, slide microscopy, segmentations, structured reports). The idc-index Python client ships the entire IDC metadata catalog as a parquet file bundled inside the pip wheel; IDCClient() loads it into DuckDB, so sql_query() runs locally with zero network calls.

Image downloads stream from public AWS S3 (default) or Google Cloud Storage buckets via the bundled s5cmd executable. No GCP/AWS credentials, no BigQuery billing, no service account JSON.

When to Use

• Searching publicly available cancer imaging datasets by modality, cancer type, anatomical site, or DICOM tag
• Building reproducible ML cohorts (segmentation, classification, multimodal) from versioned IDC releases
• Querying DICOM metadata at scale using SQL across all 175+ collections without any downloads
• Downloading specific DICOM series for local processing or model training
• Generating OHIF/Slim viewer URLs to share or inspect series interactively in a browser
• Use pydicom-medical-imaging instead when you only need to read, edit, or anonymize DICOM files that you already have locally
• For whole-slide pathology preprocessing (tiling, stain normalization) after download, use histolab instead

Prerequisites