Using smartly trained neural networks, researchers at the University of Technology Graz funded in part by NIBIB have succeeded in generating precise real-time images of the beating heart from just a few MRI measurement data. Other MRI applications can also be accelerated using this procedure. Source: TU Graz News

Research into harnessing the immune system to encourage injured tissue to regenerate has landed a Maryland researcher on a TIME magazine list of 2024 innovators. During a WTOP visit to the lab she leads at the National Institute of Biomedical Imaging and Bioengineering, researcher Kaitlyn Sadtler, explained its goal is to understand the immune system’s role in wound healing and how it could be leveraged by medical technology to regenerate tissue.

As AI is deployed in clinical centers across the U.S., one important consideration is to assure that models are fair and perform equally across patient groups and populations. To better understand the fairness of medical imaging AI, researchers trained over 3,000 models spanning multiple model configurations, algorithms, and clinical tasks. Their analysis of these models reinforced some previous findings about bias in AI algorithms and uncovered new insights about deployment of models in diverse settings.