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. 

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Perfusion CT safely diagnoses early brain death in TBI patients—but may help save others

The approach can help families make more informed treatment decisions, which can be critical for organ donation, according to authors of a new study.

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Abnormal findings affirm radiologists' key role in EVALI fight

Imaging experts can help diagnose vaping product use-associated lung injury and clear up confusion surrounding the epidemic, experts wrote in Radiology.

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Chest radiography aids diagnosis of coronavirus cluster in Vietnam

A team from Ho Chi Minh City in Vietnam recently detailed the case of a 65-year-old man who acquired the virus after traveling to Hanoi from the Wuchang district in Wuhan with his family.

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The biggest hurdles for imaging providers hoping to implement AI

AI is making a monumental impact on the way radiologists and other imaging specialists deliver care, but some providers still can’t afford to make the necessary investments at this time.  

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‘Time to act is now’: Chinese researchers confirm abnormal chest CT findings in first coronavirus patients

A number of those initially infected with the virus showed ground-glass opacities on their scans, particularly individuals who were not admitted to the ICU, researchers reported in the Lancet.

Cancer bell being rung by VA patient Anthony Thomas at Edward Hines Jr. VA Hospital. Read more https://news.va.gov/90427/cancer-patients-final-treatment-ends-victory-bell/

Experts say it may be time to stop ringing the ‘cancer bell’

This common gesture is meant to signal joy at the end of treatment, but it's producing the opposite effect for some oncology patients, according to a recent survey. 

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Does size matter? 3 key findings from a new study on developing AI for radiology research

When research teams are developing deep learning models, they have to make certain decisions about the image resolutions used in their work. For instance, should they always aim to use the largest images possible? Or are there times when smaller images can get the job done?  

Risk-based imaging most cost-effective approach in children with potential appendicitis

Utilizing more efficient imaging protocols could spare patients from unnecessary radiation while also improving value.