Researchers have developed a deep learning-based automatic detection algorithm (DLAD) that can detect malignant pulmonary nodules on chest x-rays better than physicians, sharing their findings in a new study published by Radiology.

Swedish researchers have used a novel CT imaging technique to study the soft tissue of an ancient Egyptian mummy’s hand at microscopic levels, according to a Sept. 25 study published in Radiology.

MRI scans produce mounds of unused data. Now, researchers at Washington University School of Medicine in St. Louis have created a new method of utilizing that information to determine how many and where cells have been lost due to injury or disease.

The process of episodic memory—the ability to combine memories to solve problems—may be enabled by the brain’s capacity to store, activate and connect specific memories in the hippocampus, according to new theoretical research published online Sept. 19 in Neuron.

Novel computer simulations of the female body developed by researchers from Purdue University in West Lafayette, Indiana, may help predict how more than 20 different breast tissue ratios will respond to MRI varying in radiofrequency.

A New Jersey hospital is testing an artificial intelligence (AI) device designed to alert clinicians to bleeding episodes during endovascular procedures.

Chinese researchers developed a flexible photoacoustic imaging technique by modifying fiber optic sensors and combining laser light and ultrasound to image biological tissue, detailed in a release from The Optical Society.

A deep-learning algorithm beat thoracic radiologists at classifying fibrotic lung disease, according to research published Sept. 15 in The Lancet Respiratory Medicine.