Medical imaging machinery uses a lot of power, and the extent to which it quickens the pace of global warming is becoming clearer.

Staffers with the Centers for Medicare & Medicaid Services were "attentive to the discussion and requested supporting documentation," ACR reported. 

Machine learning models could help create a more standardized, reproducible and efficient way of grading Crohn’s disease severity in the small bowel based on CT imaging. 

The model was developed and validated specifically for liver, spleen and pancreas segmentation, and outperformed a publicly available segmentation model already in use.

A general lack of awareness pertaining to ACR appropriateness criteria could be a driving factor behind the misguided requisitions, authors of a new analysis suggest. 

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

This could be especially helpful when timely clinical decisions relative to the use of a contrast agent need to be made.

With the earth’s warmest March on record in 175 years barely in the rearview mirror, a team of radiology experts says medical imaging must step up its sustainability efforts.