Solving Workflow Challenges in CT ImagingDec 9th, 2021FacebookLinkedInX (Twitter)Pinterest Add us as a preferred source on Google Onlinehttps://www.isct.org/isct-presents-webinar-seriesSolving Workflow Challenges in CT Imaging is part of a series of 12 live webinars centered on the technology and practice of CT imaging.FacebookLinkedInX (Twitter)Pinterest Add us as a preferred source on Google Latest in HomeRadiologists can identify three out of four AI-generated imagesJuly 17, 2026Women's Imaging MinnieCast, Episode 13: Partial breast irradiation in the spotlightJuly 17, 2026Radiology dominates thirty years of FDA AI device approvalsJuly 16, 2026Petition seeks to increase number of attempts for taking ARRT examJuly 16, 2026
![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)
