Artificial Intelligence

“If radiologists are expected to utilize machine learning models safely and effectively for imaging interpretation, education for all levels of background and experience will be required, and a formalized machine learning curriculum targeted toward early career radiologists and trainees is urgently needed," Monica J. Wood, MD and colleagues wrote.

A deep learning algorithm developed by researchers at the Mayo Clinic in Rochester, Minnesota, segmented abdominal CT images to determine body composition similarly to, and at times, better than trained radiologists.

An AI software system called SmartTarget—which overlays tumor information from MRI scans onto ultrasound images—may help guide surgeons in conducting biopsies and improve prostate cancer detection by reducing the number of unidentified cases, according to research publishing Dec. 5 in the journal European Urology.

Global research and development firm Cambridge Consultants, in the U.K. has developed an artificial intelligence (AI) software able to reconstruct images in real-time that have been previously damaged or obscured, according to a Dec. 4 report by Venture Beat.

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.

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.

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

Tech company Amazon has launched a new medical language processing service that, by using artificial intelligence (AI), can extract data from patient records and reports to help healthcare professionals make better treatment decisions, address data privacy and decrease overall costs, according to a report published Nov. 28 by TechCrunch.

"Neural networks, such as cycle-consistent generative adversarial network (CycleGAN), are not only able to learn what breast cancer looks like, we have now shown that they can insert these learned characteristics into mammograms of healthy patients or remove cancerous lesions from the image and replace them with normal looking tissue,” said Anton S. Becker, MD, at RSNA 2018 in Chicago.

NYU School of Medicine’s Department of Radiology announced it will release more than 1.5 million anonymous MR images from its fastMRI collaboration with Facebook AI Research (FAIR), a partnership focused on using AI to speed up MRIs.

Using artificial intelligence (AI), researchers from Stanford University in California have reduced the amount of gadolinium left behind in a patient’s body after an MRI exam, according to research presented at RSNA 2018 in Chicago