service-imaging-data-commons

Name: service-imaging-data-commons
Availability: InStock
Author: biomaps-infra

Query, download, and visualize cancer imaging data from the NCI Imaging Data Commons.

Updated Mar 13, 2026

Search Tags:#pathology #DICOM #radiology #medical imaging #AI training #cancer data #NCI IDC

Ready to run

npx skills add https://github.com/biomaps-infra/blender-opencode --skill service-imaging-data-commons

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: service-imaging-data-commons
Source: https://github.com/biomaps-infra/blender-opencode/tree/main/.opencode/skills/service-imaging-data-commons
Command: npx skills add https://github.com/biomaps-infra/blender-opencode --skill service-imaging-data-commons

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires idc-index, pandas, numpy, pydicom, webbrowser, subprocess, google-cloud-bigquery, s3fs, gcsfs, requests, simpleitk, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides access to vast public cancer imaging datasets, enabling researchers and AI developers to query, download, and visualize large-scale radiology and pathology data without authentication.

Core Features & Use Cases

Query Metadata: Search petabytes of cancer imaging data using SQL queries based on metadata like cancer type, modality, or anatomical site.
Download Data: Efficiently download DICOM files for AI training or research.
Visualize Images: View medical images directly in a browser.
Check Licenses: Understand data usage rights before incorporating data into projects.
Use Case: A researcher needs to find all CT scans of lung cancer patients from the TCGA collection to build a dataset for a new AI model. This Skill allows them to query IDC, identify relevant series, download the DICOM files, and check the data licenses.

Quick Start

Use the service-imaging-data-commons skill to find and download 10 CT scans of the chest from the nlst collection.

Frequently Asked Questions about service-imaging-data-commons

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

FAQPage Schema

How do I download public cancer imaging data for AI training?▼

You can download public cancer imaging data for AI training by querying the NCI Imaging Data Commons (IDC) metadata via SQL and retrieving DICOM files programmatically. This Skill uses the idc-index package to fetch large-scale radiology and pathology datasets without authentication.

What is the best way to query NCI IDC metadata for specific cancer types?▼

The best way to query NCI IDC metadata for specific cancer types is by executing SQL queries against the BigQuery backend. This Skill enables you to filter petabytes of radiology and pathology data by cancer type, modality, or anatomical site to identify relevant imaging series.

Can I use Python to visualize DICOM files downloaded from NCI IDC?▼

Yes, you can use Python to visualize DICOM files from NCI IDC. This Skill supports viewing downloaded medical images directly in a browser and utilizes libraries like pydicom and SimpleITK to handle and process the radiology and pathology data.

Does accessing NCI Imaging Data Commons require authentication or credentials?▼

Accessing NCI Imaging Data Commons does not require authentication to query or download public cancer imaging data. This Skill enables programmatic retrieval of DICOM files and metadata search without credentials, though you should check data licenses before incorporating datasets into projects.

What file formats and modalities are supported when downloading IDC cancer data?▼

When downloading IDC cancer data, the supported file format is DICOM and the supported modalities include large-scale radiology datasets such as CT, MR, and PET, alongside pathology images. This Skill retrieves these files using Google Cloud BigQuery and idc-index for research use.

How do I check data usage licenses for NCI IDC cancer imaging datasets?▼

You can check data usage licenses for NCI IDC cancer imaging datasets by utilizing the metadata query features within this Skill. Understanding data usage rights before incorporating public radiology and pathology DICOM files into AI projects ensures compliance with collection-specific licensing terms.