If you are not familiar with the Open Health Imaging Foundation (OHIF) Viewer — and even if you are — now is a good time to become (better) acquainted with the tool. A newly awarded grant is funding a range of enhancements that will make it even more useful for, and appealing to, radiologists and researchers in the biomedical imaging arena.
We recently spoke with Gordon Harris, PhD, director of the MGH 3D Imaging Service and head of the team that has developed the viewer, about the past, present and future of the OHIF framework. Here is what we learned.
The Viewer Is Well Suited to the Demands of Modern Radiology and Radiology Research
The OHIF Viewer is an open-source, extensible framework that allows users to create web-based imaging applications without having to recreate basic viewer functionality with each new project. Users can customize the viewer for specific workflows or work with the underlying libraries to build applications from scratch.
Using web-based applications can help overcome a host of challenges associated with using applications that can only be accessed from within hospital networks or are installed on specific workstations, challenges that often lead to performance problems and downtime. Removing these obstacles can be especially important with imaging applications that depend on access to large datasets that are time consuming to retrieve locally and require significant processing power to analyze.
With an appealing and efficient user interface and a solid, dependable code base, the OHIF framework has become the top rated open-source medical imaging software on software development platform GitHub. It has now been integrated into open-source and commercial projects across the globe.
The Viewer is Built on Nearly Two Decades of Experience
The origins of the OHIF framework can be traced to the Tumor Imaging Metrics Core at Massachusetts General Hospital, which launched in 2004 to provide imaging assessments for oncology clinical trials across the five Harvard teaching hospitals of the Dana-Faber/Harvard Cancer Center. Looking to manage the complex trials workflow, and communication between radiology and oncology teams, the developers built a web-based workflow management platform that could be accessed by study teams across sites to place orders, view results, track billing, and more. That platform is now used by 16 Cancer Centers to manage 4,200 active clinical trials with 25,000 patient visits per year.
While the workflow management platform was always web-based, the viewer was initially built by customizing and integrating an open-source workstation-based viewer that had to be installed on each PC for reviewing the images. In 2015, in order to enhance accessibility and collaboration, and minimize IT support requirements, Dr. Harris and his team decided they wanted to move the platform from the workstation-based to a web-based viewer. However, no available open-source solutions met their needs. So, in partnership with their software development consultants, Radical Imaging, they teamed up with Chris Hafey, who had developed the Cornerstone open-source web imaging libraries, and a few other like-minded colleagues and formed the Open Health Imaging Foundation (OHIF). Their goal: to build a commercial-grade, user-friendly, open-source, web-based medical imaging platform, the OHIF Viewer. The viewer development project launched the same year.
The open-source OHIF Viewer was then integrated into the clinical trials imaging informatics platform to replace the workstation-based viewer. In 2022, the clinical trials software was exclusively commercially licensed to a new company, Yunu. The development and support teams joined the company, where Dr. Harris serves part-time as co-founder and Chief Science Officer. Yunu is now expanding and further refining the software based on feedback from their broad user base. Yunu is one of hundreds of commercial and academic project building upon the OHIF open-source web viewer.
Continued Funding Will Help Meet Users’ Evolving Needs
Development of the OHIF viewer was initially funded by a combination of grants from the National Cancer Institute (NCI) and the Chan Zuckerberg Initiative, academic-industry partnerships and institutional support. While the original NCI project came to an end in 2020, Harris and colleagues applied for and were awarded a five-year sustainment grant in 2023, also from the NCI. They are now planning a variety of enhancements using the further funding.
Most notably, they will add capabilities for advanced imaging applications. These will include frameworks allowing integration of common frameworks for machine learning analysis; for server-side rendering for large datasets, such as dual-energy CT and breast tomosynthesis datasets; and for displaying, annotating and segmenting slide microscopy images. Other new tools will enable image registrations between studies, for example, and mobile-responsive design.
With other enhancements, the researchers will aim to simplify both installation and usage for end users and to improve the OHIF viewer support infrastructure.
The Platform Can Also Aid in Tackling the Challenges of Working Remotely
The COVID-19 pandemic upended ideas of the traditional workplace, with huge swaths of the US and global populations shifting to working from home during the pandemic. And the trend has continued as the world has otherwise returned to a semblance of normalcy. Today, in the US, nearly 13 percent of full-time employees do their jobs from home, according to Forbes Advisor. By 2025, the number of remote workers will reach an estimated 32.6 million: roughly 22 percent of the American workforce.
Many radiologists have joined this migration to the home office, even in the post-COVID world, when providing care remotely is no longer strictly a matter of patient and physician safety.
Working from home offers radiologists the same benefits as enjoyed by other employees following a remote or hybrid model: lower stress, better health, improved work-life balance. But it also comes with challenges. Not least of these are challenges related to using applications that can only be accessed from within hospital networks or are installed on specific workstations. “Dialing in” using VPN can help, but this also has its fair share of frustrations, especially when working with large datasets.
Here as well, the web-based OHIF framework offers a host of advantages, including image accessibility, ease of use, and the potential for collaboration and extensibility. And its benefits for radiologists working remotely will surely only improve with further development.