Artificial intelligence (AI) is an incredibly powerful tool for building algorithms that will transform the work of radiologists.
In this September 23 presentation from AuntMinnie.com's 2020 Virtual Conference, Dr. Curtis Langlotz, PhD, of Stanford University discusses the origins of AI and its applications to medical imaging. He also shows examples of real-world research that suggest how the technology may change the practice of radiology and reviews key challenges that may limit the application of AI to radiology.
Langlotz is professor of radiology and biomedical informatics and director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center) at the Stanford University Medical Center.
The future of AI in radiology: From research to the reading room
![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)
