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Version: Version 3.3 - Segmentation Support 🚧

Introduction

The Open Health Imaging Foundation (OHIF) Viewer is an open source, web-based, medical imaging platform. It aims to provide a core framework for building complex imaging applications.

Key features:

  • Designed to load large radiology studies as quickly as possible. Retrieves metadata ahead of time and streams in imaging pixel data as needed.
  • Leverages Cornerstone3D for decoding, rendering, and annotating medical images.
  • Works out-of-the-box with Image Archives that support DICOMWeb. Offers a Data Source API for communicating with archives over proprietary API formats.
  • Provides a plugin framework for creating task-based workflow modes which can re-use core functionality.
  • Beautiful user interface (UI) designed with extensibility in mind. UI components available in a reusable component library built with React.js and Tailwind CSS

OHIF Viewer Screenshot

Try the demoRelease Notes

Where to next?​

The Open Health Imaging Foundation intends to provide an imaging viewer framework which can be easily extended for specific uses. If you find yourself unable to extend the viewer for your purposes, please reach out via our GitHub issues. We are actively seeking feedback on ways to improve our integration and extension points.

Check out these helpful links:

Citing OHIF​

To cite the OHIF Viewer in an academic publication, please cite

Open Health Imaging Foundation Viewer: An Extensible Open-Source Framework for Building Web-Based Imaging Applications to Support Cancer Research

Erik Ziegler, Trinity Urban, Danny Brown, James Petts, Steve D. Pieper, Rob Lewis, Chris Hafey, and Gordon J. Harris JCO Clinical Cancer Informatics, no. 4 (2020), 336-345, DOI: 10.1200/CCI.19.00131

This article is freely available on Pubmed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259879/

or, for Lesion Tracker of OHIF v1, please cite:

LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials

Trinity Urban, Erik Ziegler, Rob Lewis, Chris Hafey, Cheryl Sadow, Annick D. Van den Abbeele and Gordon J. Harris Cancer Research, November 1 2017 (77) (21) e119-e122 DOI: 10.1158/0008-5472.CAN-17-0334

This article is freely available on Pubmed Central. https://pubmed.ncbi.nlm.nih.gov/29092955/

Note: If you use or find this repository helpful, please take the time to star this repository on Github. This is an easy way for us to assess adoption, and it can help us obtain future funding for the project.

License​

MIT © OHIF