IDC User Guide
  • Welcome!
  • 🚀Getting started
  • Core functions
  • Frequently asked questions
  • Support
  • Key pointers
  • Publications
  • IDC team
  • Acknowledgments
  • Jobs
  • Data
    • Introduction
    • Data model
    • Data versioning
    • Organization of data
      • Files and metadata
      • Resolving CRDC Globally Unique Identifiers (GUIDs)
      • Clinical data
      • Organization of data, v2 through V13 (deprecated)
        • Files and metadata
        • Resolving CRDC Globally Unique Identifiers (GUIDs)
        • Clinical data
      • Organization of data in v1 (deprecated)
    • Downloading data
      • Downloading data with s5cmd
      • Directly loading DICOM objects from Google Cloud or AWS in Python
    • Data release notes
    • Data known issues
  • Tutorials
    • Portal tutorial
    • Python notebook tutorials
    • Slide microscopy
      • Using QuPath for visualization
  • DICOM
    • Introduction to DICOM
    • DICOM data model
    • Original objects
    • Derived objects
      • DICOM Segmentations
      • DICOM Radiotherapy Structure Sets
      • DICOM Structured Reports
    • Coding schemes
    • DICOM-TIFF dual personality files
    • IDC DICOM white papers
  • Portal
    • Getting started
    • Exploring and subsetting data
      • Configuring your search
      • Exploring search results
      • Data selection and download
    • Visualizing images
    • Proxy policy
    • Viewer release notes
    • Portal release notes
  • API
    • Getting Started
    • IDC API Concepts
    • Manifests
    • Accessing the API
    • Endpoint Details
    • V1 API
      • Getting Started
      • IDC Data Model Concepts
      • Accessing the API
      • Endpoint Details
      • Release Notes
  • Cookbook
    • Colab notebooks
    • BigQuery
    • Looker dashboards
      • Dashboard for your cohort
      • More dashboard examples
    • ACCESS allocations
    • Compute engine
      • 3D Slicer desktop VM
      • Using a BQ Manifest to Load DICOM Files onto a VM
      • Using VS Code with GCP VMs
      • Security considerations
    • NCI Cloud Resources
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  1. Introduction

Google Cloud Platform (GCP)

Google Cloud Platform (GCP) is the foundation of the IDC architecture. We rely on GCP to implement the IDC functionality. IDC users can use GCP as the environment to perform the analysis of the data hosted on IDC.

Specific GCP components that we utilize and that can be useful to support cancer imaging research use cases include:

  • Compute Engine

  • BigQuery

  • Cloud Storage

  • Healthcare API

Within CRDC, Cloud Resources are intended to support CRDC users' analysis needs. In the future, we plan to develop use cases and documentation demonstrating best practices for utilizing Cloud Resources for computational tasks. In addition to the GCP components listed above, the following components are not used to support IDC functionality, but can be quite handy:

  • Colab Notebooks

  • AI Notebooks

  • DataStudio

  • Datalab

Last updated 11 months ago

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