At RSNA 2016, the key buzzwords were “deep learning,” “machine learning” and “artificial intelligence.” Vendors and major academic centers are developing a wide array of artificial intelligence neuro networks to aid radiologists in clinical diagnosis and clinical decision support. Here are two examples of how the IBM Watson system examines a mammography and cardiac patient imaging studies. Watch the VIDEO “Development of Artificial Intelligence to Aid Radiology,” an interview with Mark Michalski, M.D., director of the Center for Clinical Data Science at Massachusetts General Hospital, explaining the basis of artificial intelligence in radiology.
The most popular article in August was about advances in fractional flow reserve (FFR) technologies. The image shows Philips' new version of its iFR system that displays hemodynamic pressure drop points in an overlay on live angiographic images, matching up the iFR readings with corresponding lesions.