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University Children's Hospital Zurich
This project offers a Urography analysis platform with user-friendly segmentation tools, automated server-based analysis, and interactive time course plots. It includes a comprehensive report feature for summarizing images, data, statistics, demographics, and clinician notes, with options to export as a PDF or send directly to PACs.
The Cancer Imaging Archive
The Cancer Imaging Archive (TCIA), funded by the US National Cancer Institute, publishes de-identified cancer medical images. Hosting 200+ collections with 70,000+ subjects, it provides supporting data like patient outcomes and treatment details.
ProstateCancer.ai
ProstateCancer.ai, an application that utilizes the Open Health Imaging Foundation (OHIF) viewer, showcases the seamless integration of artificial intelligence (AI) models with medical image interaction and manipulation.
Research Viewer for Clinical Trials in Nuclear Medicine
Pixilib utilizes OHIF for a portable PET/CT viewer, integrating it with a backend for data management. It aids clinical trials with advanced quantification of biomarkers and future AI diagnosis tools.
Gradient Health Breast Density
Breast Density Classification by Gradient Health uses Google Sheets and OHIF to categorize breast density in mammograms, with the goal of aiding early breast cancer detection. It utilizes mammogram images for training a deep learning model.
NCI Imaging Data Commons
NCI Imaging Data Commons (IDC) is a cloud-based environment containing publicly available cancer imaging data co-located with analysis and exploration tools and resources.
The Medical Imaging Data Resource Center (MIDRC)
The Medical Imaging and Data Resource Center (MIDRC) is a multi-institutional initiative driven by the medical imaging community and aimed at accelerating the transfer of knowledge and innovation in the current COVID-19 pandemic.
XNAT
XNAT has a significant track record with considerable international traction in the imaging research community and is widely used for managing the imaging component of observational clinical studies. Seamless integration of OHIF with XNAT combines an outstanding general-purpose, zero-footprint PACS-like viewer with cutting-edge research functionality.