A research team compiled of mathematicians, clinicians and imaging technicians from the University of Southampton in the U.K. recently developed a computational method to analyze x-ray images of the lungs for overall function and presence of fatal diseases.

EnvoyAI today announced a new integration with Insignia Medical Systems’ InSight PACS to provide artificial intelligence (AI)-enhanced imaging workflows to customers.

The U.S. leads 22 comparable countries in MRI price, availability and use, according to a data report published by the Kaiser Family Foundation. The report was recently presented at a forum held by the Kaiser Family Foundation and the Peterson Center on Healthcare in Washington, D.C.

When testing for prostate cancer, multiparametric MRI with or without targeted biopsy was more effective than the common standard transrectal ultrasonography-guided biopsy, but a recently published editorial argues more testing is needed.

On May 8, the Journal of the American Medical Association released an update to the 2012 U.S. Preventive Services Task Force (USPSTF) recommendation regarding prostate-specific antigen (PSA)-based screening for prostate cancer.

Bibb Allen Jr., MD, chief medical officer with the American College of Radiology (ACR)’s Data Science Institute (DSI) talked with HealthImaging about focusing Medical Image Computing and Computer Assistance Intervention's (MICCAI) artificial intelligence (AI) challenges on radiologists' clinical needs.

Contrary to popular belief, a study carried out by researchers from the University of Miami, the University of California Davis, Columbia University and the National Institute of Neurological Diseases and Stroke may suggest that depression doesn't significantly affect one's memory and cognition.

A new artificial intelligence (AI) tool lets scientists visualize a three-dimensional (3D) model of living human cells, even when the entire cell is not visible, according to a recent NPR story.

Through MRI analysis, researchers from Duke University found poor communication between multiple regions in the brain's visual cortex increases the risk of developing mental illness.

Using genomic sequencing to identify mutations in emerging strains of bacteria responsible for or at-risk of causing an outbreak is time consuming and labor-intensive. However, researchers have recently developed a new machine learning tool that can speed up the process.