The University of California, San Francisco (UCSF) is launching a new center to accelerate the use of artificial intelligence (AI) technology in radiology.
UCSF's Center for Intelligent Imaging (ci2) will develop and apply AI to devise new ways to view the internal body and evaluate health and disease. Center researchers will use patient images and clinical data from UCSF Health and other institutions to develop, test, and validate deep-learning algorithms.
Also, the center will link academic innovation to startups to promote collaborative AI imaging research and development. London-based startup Kheiron Medical Technologies will work with the UCSF breast imaging group to ensure that its Mia breast cancer screening software can be safely and feasibly deployed in ethnically diverse populations.
Graphics processing unit technology developer Nvidia will help the center build infrastructure and tools that will enable the translation of AI into clinical practice.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
