U.K. ultrasound training developer MedaPhor announced the first pilot of its ScanNav real-time image analysis software at a London hospital.
The pilot will take place in the fetal medicine department of St. George's University Hospitals National Health Service (NHS) Trust.
Initially targeted at the U.K. pregnancy screening program, which is offered to all women at 20 weeks of pregnancy, ScanNav evaluates more than 50 individual criteria to verify that the six views required by the NHS Fetal Anomaly Screening Programme are complete and fit for purpose.
ScanNav uses deep-learning technology to assess the same features sonographers look for in ultrasound images, the firm said. The system has "learned" this using more than 350,000 images assessed by a panel of senior sonographers. Initial validation studies have shown the artificial intelligence (AI) system is as good as an expert colleague in providing peer review, MedaPhor 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.auntminnieeurope.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)
