United Imaging has formed a research collaboration with Massachusetts General Hospital (MGH) aimed at developing artificial intelligence (AI) technology for imaging of patients with COVID-19.
United's AI teams in Boston and Shanghai will collaborate with an MGH group led by Jayashree Kalpathy-Cramer, PhD, to develop AI algorithms that can be applied to standard x-ray images, according to the vendor.
After being trained using data from a large CT database, these models will then be refined with x-rays from U.S. patients in hopes of creating algorithms for detecting and quantifying COVID-19 and estimating its severity, United said. Other potential use cases will also be explored.
![Axial images from unenhanced calcium score cardiac CT (left) and curved planar reformation images from CT angiography (right) show that higher long-term exposure to air pollution is associated with greater coronary artery calcium and more obstructive coronary artery disease (CAD). Top row: Images in a 68-year-old male patient with higher 10-year mean ambient air pollution exposure (7.9 μg/m3 for particulate matter measuring ≤2.5 μm in diameter [PM2.5] and 17.4 parts per billion [ppb] for NO2) with extensive CAD (coronary artery calcium score [CACS] >1,000 and obstructive CAD [≥70% diameter stenosis]). Bottom row: Images in a 57-year-old female patient with lower 10-year mean ambient air pollution exposure (6.3 μg/m3 for PM2.5 and 4.6 ppb for NO2) with no CAD (CACS = 0 and no obstructive stenosis).](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/06/hanneman.r6SMLzkezo.png?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
