New architecture disaggregates resources to give customers the freedom to scale in any direction, unlocking the most diverse set of workloads while providing investment protection.

With the help of AI, technologists at a hospital in Guyana were able to reduce mammographic positioning error rates from 20% to 5%.

In addition to CE-MRI's increased sensitivity for identifying breast cancers, the researchers also found the modality had superior negative likelihood ratios with higher pre-test probabilities for safely ruling out malignancy. 

The funds will be allocated specifically toward neuroimaging and cognitive and immunological tests to explore if and how mild and asymptomatic SARS-CoV-2 infections have a long-lasting impact on neurocognitive function. 

A new analysis suggests that follow-up imaging protocols for certain lung nodules identified via CT may need to be revisited. 

Brian Ghoshhajra, MD, division chief, cardiovascular imaging, Massachusetts General Hospital, explains what specialized training is needed to perform coronary computed tomography angiography (CCTA) as interest rapidly rises in this field. 

Combining CT lung measurements with machine learning models to predict prognosis in COPD patients could help to lessen their reliance on emergency services. 

The group is advocating for the NRC to treat significant extravasations in the same manner as any other reportable medical event. 

Artificial intelligence vendor DiA has emerged as a key third-party provider of AI to larger imaging vendors.

Recently, experts explored the efficacy of two deep learning models for grading COPD severity based on chest radiographs—a method that has not yet been thoroughly tested.