A University of Southern California team has created an artificial intelligence (AI) algorithm adept at slowing the spread of infectious diseases, while simultaneously considering resources and population dynamics.

According to survey results recently published online in the Journal of the American College of Radiology, more than one-third of radiologists lack exposure to artificial intelligence (AI) educational material and resources. Additionally, most trainees' desire to learn about or pursue diagnostic radiology is hindered by AI's role in medicine.

Healthcare startup Aidoc has announced the world’s first comprehensive, full-body artificial intelligence (AI) platform to analyze CT scans, according to Technology Networks.

A University of Saskatchewan team has created a deep learning technique that demonstrated enhanced de-noising capabilities in low-dose CT (LDCT) imaging, resulting in little resolution loss and better performance, according to a study published in the Journal of Digital Imaging.

Radiation therapy is an integral part of many cancer treatments. Ideally, doses are focused on the observable tumor while leaving surrounding organs unaffected, but determining the figuration of tumors and organs-at-risk is done manually—a time consuming and, at times, imprecise task for radiologists.

A new broad oncology deep learning suite from the cloud-based medical imaging software solutions company Arterys Inc. was approved for 501(k) clearance by the FDA, according to a report by Business Insider.  

A Northeastern University-Boston professor and his students have used magnetic nanoparticles to create “beautiful images with unprecedented clarity” of the human brain, reports News@Northeastern.

When you close your eyes and visualize an important moment from the past, your brain may use the same eye movement patterns to reconstruct images long after you’ve originally seen them. It may seem like science fiction, but a study published in Cerebral Cortex found evidence of the phenomena.