Philips Healthcare and the U.S. Department of Homeland Security's Industrial Control Systems Cyber Emergency Response Team (ICE-CERT) issued security advisories regarding vulnerabilities to Philip's medical imaging management software systems ISite and IntelliSpace PACS.

Just because a patient receives two imaging exams that are exactly the same doesn't guarantee the billing will match. A Florida man had first-hand experience with this—being charged 33 times more for a second CT scan than his first, according to an April 9 article in NPR's "Bill of the Month" series.

RadNet recently expanded its California footprint by acquiring five imaging centers in the Fresno area, making it the leading non-hospital-based outpatient imaging operator in the region, according to an April 6 release.

A team of international researchers published a study in Radiology that found surface regularity taken from high-resolution contrast-enhanced pretreatment volumetric T1-weighted MRIs to be an accurate predictor of survival in patients with specific malignant brain or spine tumors.

New research published online April 3 in Radiology found that mammography recall rates are correlated with higher rates of breast cancer detected between screenings.

Radiology staffing shortages are hitting Waikato Hospital in New Zealand. Its workforce problem led a department of health board executive to label the unit as “vulnerable” and has prompted the hospital to look for imaging specialist overseas, according to an April 5 article in Stuff.

Columbia University researchers recently found that the human brain continues to produce hundreds of new neurons every day, even into old age, according to an article by the Los Angeles Times.

Deep learning and artificial intelligence (AI) are often associated with identifying nodules and classifying images, but a recent study found convolutional neural networks (CNNs) can be utilized in radiology workflows to determine musculoskeletal MRI protocols.

Calling the discovery of a new organ in the human body surprising is a bit of an understatement, but that's what a study published in Scientific Reports claims.

A team of Stony Brook University-led researchers in New York created a method using deep learning digital pathology to map cancerous immune cell patters that may help guide new cancer therapies.