A machine able to interpret diagnostic imaging studies better than radiologists has long been foreseen, yet its arrival comes almost as a surprise. We have underestimated the potential of AI to perform the kinds of work we do.

Despite authoritative voices reassuring radiologists that artificial intelligence will never seriously cull their workforce, speculation to the contrary continues. In fact, some of the prognosticators most certain about likely job losses are radiologists themselves.

The University of Saskatchewan recently held a patient engagement workshop dedicated to AI and found that some consumers still harbor anxieties about its unknown elements. 

University College London researchers harnessed this new tool to quickly analyze cardiovascular magnetic resonance images and determine the risk of other adverse events such as stroke.

Caption Guidance serves as an accessory to certain diagnostic systems, aiding clinicians in capturing high-quality cardiac scans. 

South Korean researchers recently tested the clinical tool in a retrospective study of more than 170,000 mammography exams.

Chun Yuan beat out the competition by using cloud-computing tools and AI to predict cardiovascular risk through magnetic resonance knee scans. 

Disrupters such as Google and Walmart are turning healthcare upside down, and imaging is no exception. 

A new deep learning tool, developed by UT Southwestern, could potentially eliminate harmful delays in the delivery of radiation therapy. 

Halo Diagnostics announced Jan. 30 that it’s teaming up with several California providers in a bid to take the speciality "to the next level."

Located within its North American headquarters, the hub would pursue radiology-related research and development to create the next generation of diagnostic technology. 

Ohad Arazi will assume the role of chief executive at the Israel-based company on March 1, replacing co-founder Eyal Gura.