Medical Imaging

Physicians utilize medical imaging to see inside the body to diagnose and treat patients. This includes computed tomography (CT), magnetic resonance imaging (MRI), X-ray, ultrasound, fluoroscopy, angiography,  and the nuclear imaging modalities of PET and SPECT. 

GE Healthcare ramping up CT, x-ray system production to address ‘unprecedented demand’ during pandemic

The Chicago-based imaging giant said the increase in manufacturing capacity will also include greater output of ultrasound devices, patient monitors and ventilators.

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PSMA PET/CT tops conventional imaging for pinpointing high-risk cancer

Australian researchers also recommended updating current diagnostic pathways to incorporate the new molecular imaging approach.

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X-ray emerges as frontline tool for coronavirus: 3 lessons from radiologists battling the pandemic

Chest imaging experts at the center of the U.K.'s COVID-19 outbreak shared their early learnings in a new BMJ opinion piece.

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Many patients have COVID-19 lung abnormalities at discharge; follow-up imaging may be necessary

More than 90% of individuals with the new virus still had lingering irregularities on their CT scans when they left the hospital, experts wrote recently in Radiology.

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New MRI contrast agent detects cancers before they spread to the brain

The material increases magentic resonance sensitivity so that providers can visualize abnormal tissue changes indicative of metastasis.

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Canon scores FDA clearance for artificial intelligence engine that bolsters MRI quality

The Advanced Intelligent Clear-IQ Engine harnesses deep learning to help radiologists differentiate true magnetic resonance signals from noise. 

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COVID-19 recoveries: The evolution of CT abnormalities from onset to discharge

A group of Chinese physicians tracked lung abnormality changes in five patients from hospital admission to discharge, sharing their findings in the Korean Journal of Radiology.

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Neural network stages knee osteoarthritis on x-rays better than MSK radiologists

“These findings suggest that our algorithm approaches the upper bound of possible performance of an experienced radiologist,” experts wrote Wednesday in Radiology: Artificial Intelligence.