A new analysis conducted by researchers at McKinsey & Company in New York, published Dec. 4 in the Journal of the American College of Radiology, identified artificial intelligence (AI) and blockchain as the focus for most global medical imaging startups, and potentially for the future of medical imaging.

A deep learning-based approach accurately predicted aneurysm size from magnetic resonance angiography (MRA) images, reported the authors of a Dec. 3 study published in the Journal of Digital Imaging.

New software that uses artificial intelligence (AI) to diagnose chronic thromboembolic pulmonary hypertension (CTEPH) will receive an expedited review from the FDA as part of the agency’s breakthrough devices program. The program, first established in 2017 as part of the 21st Century Cures Act, is designed to speed up the development of devices and ensure timely patient access.

Artificial intelligence (AI) is sure to change radiology, but a recent feature in IEEE Spectrum argues its true effect on medicine will be felt not in imaging, but in the pathology lab.

A three-dimensional (3D) deep residual network accurately detected and classified cerebral microbleeds (CMBs) on susceptibility-weighted magnetic resonance images (SWIs), reported a team of San Francisco-based researchers.

There is relatively little understood about infant brain development. A team of Finnish researchers sought to explore the brain structures of newborns in a new study published in Brain Structure & Function.

Sunrise, Florida-based medical group Mednax announced it is launching an artificial intelligence (AI) incubator focused on creating innovative radiology solutions.

Using a variation of an unconventional imaging approach called “ghost imaging," an international team of researchers has successfully taken low dose three-dimensional (3D) x-ray images which may help make screening for early signs of diseases and cancer cheaper, safer and more accessible.