Medical Imaging

AI can detect brain hemorrhages in CT scans more accurately than some radiologists, according to new findings published by Proceedings of the National Academy of Sciences.

Deep learning algorithms can be trained to flag suspicious chest x-rays in an emergency department (ED) setting, according to new research published in Radiology.

Working alongside machine learning technology can help radiologists detect more breast cancers, according to new findings published in IEEE Transactions on Medical Imaging.

Medical imaging professionals and radiation experts are in a position to play a significant role as AI technologies continue to evolve, according to a new commentary published in the Journal of Medical Imaging and Radiation Sciences.

Sanford, Florida-based Omega Medical Imaging announced that its new FluoroShield radiation reduction system has received FDA approval.

A new AI system is able to identify pneumothorax more accurately than many radiologists.

Researchers from NVIDIA and King’s College London have collaborated on a new federated learning system specifically designed for the interpretation of medical images.

The newest AI-based imaging processing software from Subtle Medical has received FDA clearance.

The University of California San Francisco (UCSF) is developing a new center dedicated to applying AI to the field of radiology and improving patient outcomes.

Machine learning (ML) algorithms could potentially be trained to alter mammography findings, tricking radiologists into make an incorrect diagnosis, according to new research published in the European Journal of Radiology.

Sensyne Health announced Thursday, Oct. 10, that it has joined Bayer’s newest innovation hub, LifeHub UK, and will work toward developing solutions for automated image evaluation.

AI can improve CT findings and play a key role in the evaluation of hypovascular hepatic metastases, according to a new study published in Radiology: Artificial Intelligence.