Artificial intelligence (AI) support systems for reading mammograms can improve a radiologist’s ability to detect cancers, according to a new study published in Radiology. Using the system, the authors added, does not lengthen the overall reading time.

Stanford University researchers have produced a convolutional neural network capable of finding most of 14 different disease states—nearly everything from pneumonia to lung cancer—on chest x-rays.

State Reps. Angie Hatton and Robert Goforth have pre-filed legislation to roll back portions of Kentucky’s House Bill 2, which barred federally certified radiologists from reading x-rays in black lung compensation cases.

The American Medical Association (AMA) shared its seven most competitive medical specialties of 2018, and the list included integrated interventional radiology.

Aidoc and SaferMD are joining forces for a new solution that will use artificial intelligence (AI) to improve clinical results and give radiologists higher Medicare Merit-Based Incentive Payments System (MIPS) scores.

Last spring RBJ put out a call for entrants to compete in its inaugural Imaging Innovation Awards. We opened the contest to all private radiology practices and hospital radiology departments that had recently completed a project combining creative thinking with coordinated teamwork to develop a notably original breakthrough in some particular aspect of medical imaging.

The Southeast Regional Stroke Center at Erlanger, based out of the University of Tennessee’s Erlanger Medical Center in Chattanooga, receives referrals from more than 40 hospitals and treats more than 2,500 strokes each year. Patients are rushed to their internationally-recognized center, more commonly referred to as the Erlanger Stroke Network, both day and night, some arriving by ambulance and others by helicopter.