Intel and GE Healthcare* are teaming up to deliver artificial intelligence (AI) solutions across multiple medical imaging formats to help prioritize and streamline patient care.

"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.

As time goes on, artificial intelligence (AI) is becoming more widely accepted as a necessary component of clinical workflow in medical imaging. According to Tarik K. Alkasab, MD, PhD, a radiologist at Massachusetts General Hospital in Boston, AI has the potential to make radiology reporting much more consistent and ultimately help radiologists make smarter decisions.

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.

One season of football may cause alterations in the brain development of younger players, according to research presented Monday, Nov. 26, at RSNA 2018 in Chicago.

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

During her speech Sunday, Nov. 25, at the opening session of RSNA 2018 in Chicago, RSNA President Vijay Rao, MD, noted that today's radiologists will be empowered by new technologies, not replaced by them. 

Artificial intelligence (AI) is changing how radiologists think about and perform studies, so it’s no surprise AI and machine learning will take center stage this year at RSNA 2018 in Chicago.