imaging-data-commons

Query and download cancer imaging data from the NCI Imaging Data Commons using the idc-index Python package.

2|Updated Jun 4, 2026
One-click install
npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill imaging-data-commons-lord1egypt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: imaging-data-commons
Source: https://github.com/Lord1Egypt/scientific-agent-toolkit/tree/main/scientific-skills/imaging-data-commons
Command: npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill imaging-data-commons-lord1egypt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires idc-index, pandas, numpy, pydicom, and includes references (resource) components.

What problem does it solve?

This skill solves the complexity of navigating, querying, and downloading large-scale public cancer imaging datasets from the National Cancer Institute Imaging Data Commons (IDC) without requiring authentication or manual browser-based selection.

Core Features & Use Cases

  • Metadata Discovery: Perform complex SQL queries across IDC index tables to filter radiology (CT, MR, PET) and pathology datasets by cancer type, modality, or anatomical site.
  • Efficient Data Retrieval: Download specific subsets of DICOM data or entire collections directly from cloud storage buckets using optimized tools.
  • Use Case: A researcher needs to build a training dataset of lung CT scans from the NLST collection; this skill allows them to filter by modality and body part, verify licenses, and download the specific series directly to their local environment.

Quick Start

Use the imaging-data-commons skill to query the IDC index for all CT scans of the chest in the rider-pilot collection and download them to the data directory.

Frequently Asked Questions about imaging-data-commons

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query public cancer imaging data from the NCI Imaging Data Commons?

You can query public cancer imaging data from the NCI Imaging Data Commons by running SQL queries across IDC index tables to filter datasets by cancer type, modality, or anatomical site without needing authentication.

How do I download DICOM files from the Imaging Data Commons to a local environment?

You can download DICOM files from the Imaging Data Commons by retrieving specific subsets or entire collections directly from cloud storage buckets using optimized tools to save them locally.

Can I use SQL to filter IDC radiology datasets by modality and body part?

Yes, you can use SQL to filter IDC radiology datasets by modality and body part, querying index tables to discover specific collections, patients, and series for research.

Do I need an account or authentication to access NCI IDC datasets?

No, you do not need an account or authentication to access NCI IDC datasets, as the skill facilitates navigation and downloading of public cancer imaging data directly.

What is the best way to build a training dataset of lung CT scans from IDC collections?

The best way to build a training dataset of lung CT scans is to filter IDC collections by modality and body part, verify licenses, and download specific series directly to your environment.

Does this skill support browser-based visualization for pathology and radiology research?

Yes, this skill supports browser-based visualization for pathology and radiology research, facilitating metadata discovery and DICOM file retrieval from the NCI Imaging Data Commons.