Enhanced Open-Source Zero-Footprint Web Viewer for Imaging Research

Project Summary/Abstract The Open Health Imaging Foundation (OHIF) Viewer and its libraries, including Cornerstone3D, provide a professional-grade, open-source framework for web-based imaging informatics in cancer research and medical imaging applications. With features such as image review, annotation, segmentation, and a user-friendly interface, OHIF empowers researchers and developers to create custom imaging tools, integrate innovative extensions and workflow modes, and transition traditional desktop platforms to modern, cloud-based solutions. Delivered through a zero-footprint web architecture, the platform eliminates the need for local software installations, significantly improving accessibility and usability. These foundational capabilities were developed under prior grants from the NCI Informatics Technology for Cancer Research (ITCR) U24 program, enabling OHIF to become a leader of imaging informatics for cancer research and beyond. Despite these advancements, further work is required to ensure the platform remains robust, interoperable, and sustainable as it continues to grow and serve an expanding user base. Key challenges include improving reliability in the face of rapid feature development, integrating the platform more seamlessly into modern healthcare IT ecosystems, and addressing the maintenance and modernization needs of critical underlying libraries. These improvements are essential to keep pace with evolving research and clinical demands while continuing to foster a thriving community of contributors and users. To address these challenges, this project will focus on enhancing the testing ecosystem for the OHIF Viewer and Cornerstone3D to ensure reliability across devices and workflows, while supporting sustainable community contributions. Additionally, building on top of the Fast Healthcare Interoperability Resources (FHIR) standard, we will enable real-time interoperability between the Viewer and other healthcare systems, such as measurement reporting systems, streamlining collaboration and synchronization of data. Finally, modernization and harmonization of key libraries, including dcmjs and dicom-parser, will improve performance and long-term usability, ensuring the platform’s continued relevance and impact. By addressing these priorities, this project will enhance the sustainability, usability, and impact of the OHIF platform, empowering cancer researchers and the broader biomedical research community with reliable, scalable, and interoperable imaging tools. These advancements will facilitate collaborative research, improve the integration of imaging data with other healthcare systems, and support the NIH’s vision of fostering robust, FAIR-compliant software tools for modern biomedical research.