Mallinckrodt Institute of Radiology at Washington University (WashU) School of Medicine in St. Louis, MO, has established a new Center for Computational and AI-enabled Imaging Sciences.
The center, led by Mark Anastasio, PhD, will focus on developing AI-based medical imaging applications that integrate information from various imaging modalities. It will also support training for clinicians and researchers and work in partnership with WashU's McKelvey School of Engineering.
In an announcement, WashU Medicine highlighted two software packages from the WashU pipeline: a breast cancer prediction tool intended for mammography and an AI-based brain-mapping software designed to enhance the precision of neurosurgeries. Both are currently in the process of commercialization, WashU said.
![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)
