imaging-data-commons
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
npx skills add BioTender-max/awesome-bio-agent-skills --skill imaging-data-commons --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Uses the idc-index Python package to query and download public cancer imaging data from the NCI Imaging Data Commons. It enables querying by metadata, downloading DICOM files, and visualizing in a browser, with no authentication required.
How it works
- Ensure idc-index is installed (pip install --upgrade idc-index).
- Create an IDCClient instance and run client.sql_query() to query the index for metadata (e.g., collection stats).
- Call client.fetch_index("collections_index") or other tables (e.g., analysis_results_index) for richer metadata.
- Use client.download_from_selection() to download DICOM files from a selected subset.
- Visualize in browser with client.get_viewer_URL(seriesInstanceUID=...).
- Confirm IDC data version (client.get_idc_version()) and verify it matches v23, upgrading idc-index if needed.
- Verify licensing and data licenses before use, referencing IDC data licensing guidelines.
When to use it
- Finding publicly available radiology or pathology images
- Selecting image subsets by cancer type, modality, or metadata
- Downloading DICOM data from IDC
- Visualizing medical images in a browser without a local DICOM viewer
What it can touch
- Idc-index package and IDCClient API for querying, fetching index data, and downloading data
- DICOM files downloaded via idc-index workflow
- Browser-based image viewer URLs generated by get_viewer_URL
Caveats
- IDC data licensing applies to data usage; data licenses must be respected when using the data
- Requires verification that IDC data version is v23; upgrade idc-index if the installed version is older than 0.11.14
- Hardware/network requirements not specified; follow installation and environment recommendations in the installation section
# Imaging Data Commons ## Overview Use the `idc-index` Python package to query and download public cancer imaging data from the National Cancer Institute Imaging Data Commons (IDC). No authentication required for data access. **Current IDC Data Version: v23** (always verify with `IDCClient().get_idc_version()`) **Primary tool:** `idc-index` ([GitHub](https://github.com/imagingdatacommons/idc-index)) **CRITICAL - Check package version and upgrade if needed (run this FIRST):** ```python import idc_index REQUIRED_VERSION = "0.11.14" # Must match metadata.idc-index in this file installed = idc_index.__version__ if installed < REQUIRED_VERSION: print(f"Upgrading idc-index from {installed} to {REQUIRED_VERSION}...") import subprocess subprocess.run(["pip3", "install", "--upgrade", "--break-system-packages", "idc-index"], check=True) print("Upgrade complete. Restart Python to use new version.") else: print(f"idc-index {installed} meets requirement ({REQUIRED_VERSION})") ``` **Verify IDC data version and check current data scale:** ```python from idc_index import IDCClient client = IDCClient() # Verify IDC data version (should be "v23") print(f"IDC data version: {client.get_idc_version()}"
- Overview
- When to Use This Skill
- Quick Navigation
- IDC Data Model
- Index Tables
- Available Tables
- Joining Tables
- Clinical Data Access
- Data Access Options
- Installation and Setup
- Core Capabilities
- 1. Data Discovery and Exploration
- 2. Querying Metadata with SQL
- 3. Downloading DICOM Files
pip install --upgrade idc-index pip install pandas numpy pydicom Download entire collection idc download rider_pilot --download-dir ./data Download specific series by UID idc download "1.3.6.1.4.1.9328.50.1.69736" --download-dir ./data Download multiple items (comma-separated) idc download "tcga_luad,tcga_lusc" --download-dir ./data Download from manifest file (auto-detected) idc download manifest.txt --download-dir ./data
What does the imaging-data-commons skill do?
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill imaging-data-commons --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.