Specialists can improve aneurysm detection rates by using a deep learning algorithm that provides a second assessment of images already interpreted by radiologists, according to new findings published in Radiology.

Two Egyptian mummies pinned unidentifiable by archaeologists have recently been given three-dimensional (3D) faces with the help of CT imaging and computer animation thanks to researchers at Johns Hopkins University in Baltimore, according to a report published Oct. 23 by The Baltimore Sun.

Engineers from MIT in Cambridge, Massachusetts have developed a non-invasive MRI sensor no bigger than a penny that can detect and measure electrical activity or optical signals in the brain, according to a recent MIT news release. The research was published online Oct. 22 in Nature Biomedical Engineering.

When imaging brain tumors such as gliomas, machine learning may advance the use of imaging and augment clinical care for patients, according to a review published Oct. 17 in the American Journal of Roentgenology—specifically in tumor segmentation and MRI radiomics.

Health technology company Royal Philips has launched its global incubator program for startup companies looking to apply artificial intelligence (AI)-based solutions into healthcare.

Researchers and scientists with the Montefiore Medical Center in Bronx, New York, are developing an artificial intelligence (AI) tool to identify patients with a deadly lung condition.

The color scale used to optimize image interpretation has a measurable diagnostic effect on the interpretation of computed tomography perfusion (CTP) exams and apparent diffusion coefficient (ADC) images, according to an Oct. 15 study published in Clinical Radiology.

MRIguidance, a spin-off company of the University Medical Center Utrecht in the Netherlands, is developing an advanced MRI software that can characterize both soft tissue and bone without the use of radiation, according to a company news release published Oct. 16.