The profession of radiology may rightly regard 2017 as an extended coming-out party for AI within the specialty. At ACR’s annual meeting in May, the keynote speeches all revolved around the changes AI will bring. AI occupied an entire quadrant of space, including a dedicated stage, at the RSNA annual meeting in the fall. Seemingly dozens of startups, along with numerous established companies, lined up in vendor booths ready to dazzle you with the next generation of radiology technology.

With few exceptions, the most attention-demanding discussions about how and when artificial intelligence will transform radiology have been led by—and largely held within—the academic sector. That’s not surprising, given that teaching radiologists are the ones doing the research, blazing the trails and comparing the notes.

While three-dimensional printing has been used in various industries for more than three decades, it took medicine just three or so years to catapult the technology into the popular imagination. Among burgeoning areas of healthcare innovation, probably AI alone has made more headlines in that short a span. And life-size models of individual patients’ organs, which allow surgeons to carefully plan complex procedures and consult with patients and families, are just the start.

A robotic needle-placement system outfitted with correction software to improve its accuracy in mechanizing computed tomography (CT)-guided needle placement, according to a study published ahead of print in the Journal of Vascular and Interventional Radiology.

Densitas, a medical device company based out of Halifax, Nova Scotia, Canada, announced that DENSITAS|density, its software that uses machine learning to produce breast density reports, has gained FDA clearance.

Elad Walach, founder and CEO of the medical imaging company Aidoc, is one of many in the industry who believes radiology will be transformed by artificial intelligence (AI) sooner rather than later. He went into detail on the topic in a new column published in Forbes.

Radiology supercomputer “Project Clara” could improve imaging quality while speeding up the detection of fatal diseases like cancer and heart failure, Forbes has reported.

Despite radiology’s love-hate relationship with artificial intelligence (AI), advancements could afford the field an opportunity to “hit refresh” and reinvent itself, Emory University professor and radiologist Srini Tridandapani, PhD, MD, MSCR, wrote in Academic Radiology this month.