A deep learning technique was able to detect glaucoma with more accuracy than traditional approaches, according to a recent study conducted by IBM and New York University scientists.

A deep-learning (DL) algorithm was able to assess mammographic breast density at the level of an experienced mammographer, according to a study published in Radiology.

PACS is powering better workflow in breast imaging, transforming the way breast imaging radiologists read studies and interact with one another by improving physician efficiency, accuracy and saving time. Metrics matter in healthcare today and now excellent efficiency, productivity, quality of care and provider and patient satisfaction are measures of success that belong together in the pursuit of better breast imaging.

Having been in the Sectra PACS fold since 2004, members of the radiology department at six-hospital CoxHealth in Springfield, Mo., didn’t need much convincing to “VNAble” their existing system so it could handle cardiology workflows on top of their own.

The global market for artificial intelligence (AI) in medical imaging is expected to see significant growth in the years ahead, topping $2 billion by 2023, according to a new report from Signify Research.

Wayne, NJ, June 5, 2018 – Konica Minolta Healthcare Americas, Inc., a recognized leader in medical imaging systems and healthcare IT, announces the introduction of AeroRemote™ Insights, a cloud-based, business intelligence and analytics solution that delivers detailed information on asset utilization, department workflow and efficiency, system health and more. AeroRemote Insights provides daily performance data in intuitive visual formats that managers can utilize to optimize department performance and manage digital radiography assets. This new service also enables managers to act on urgent situations immediately and respond to usage trends intelligently.

Building the infrastructure to support the accelerating adoption of AI in healthcare is the mission of Pure Storage and its FlashBlade technology, an all-flash scale-out object-based solution that can expand to petabytes of capacity. As Esteban Rubens says, infrastructure to power AI, machine learning and deep learning needs to be effortless, efficient and evergreen to ensure success today and into the future. Here’s how.

When it comes to teaching new dogs new tricks, radiology training programs need to be thinking about updating their curricula and preparing for both the short- and the long-term effects of AI and machine learning, according to “Toward Augmented Radiologists,” a new commentary published online in March in Academic Radiology.