France-based Median Technologies will showcase its developments for eyonis alongside the company's AI-powered clinical trial imaging services at the 2024 European Congress of Radiology (ECR) in Vienna, from 28 February to 3 March.
At ECR 2024, the company will give two Lightning Talk presentations as well as have a scientific poster available for viewing. These include the following:
- “Eyonis LCS: Revealing Independent Verification Results & Advancements in Clinical Validation Studies," AI Theater Industry Sessions/AI Lightning Talks 2 (AI exhibition, Expo X1), 28 February, 12:30 p.m. CET.
- “Eyonis AI tech-based CADe/CADx device suite: unveiling independent verification results in Lung Cancer Screening & preliminary Hepatocellular carcinoma diagnosis results," AI Theater Industry Sessions/AI Lightning Talks 5 (AI exhibition, Expo X1), 29 February, 12:50 p.m. CET.
- Scientific poster “Developing a novel computer-aided diagnostic technique based on deep learning and CT images for early HCC diagnosis."
Median’s eyonis and iCRO/Imaging Lab teams will be available at booth #AI-17, AI Exhibition, Expo X1 for the duration of the industry exhibition.
![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&fit=crop&h=100&q=70&w=100)
![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)
