Explore more about: Magnetic Resonance Imaging (MRI)

NIBIB-funded researchers have developed a way to use artificial intelligence to speed up MRI imaging without sacrificing quality.

The National Institutes of Health has launched an ambitious effort to use artificial intelligence, computation, and medical imaging to enable early disease detection, inform successful treatment strategies, and predict individual disease outcomes of COVID-19.

NIH has granted Sandia $6 million to build the prototype medical device that would make magnetoencephalography (MEG) — a type of noninvasive brain scan — more comfortable, more accessible and potentially more accurate.

With his election this past February to the National Academy of Engineering (NAE), NIH’s Peter Basser achieved one of the highest professional distinctions accorded to any engineer.

A team created an adaptable, wearable and stretchable fabric embroidered with conductive threads that provides excellent signal-to-noise ratio for enhanced MRI scanning.

Neurologists have observed reduced neural activity during non-rapid eye movement sleep (NREM). Now MRI imaging during NREM reveals an exchange between brain blood and cerebrospinal fluid that may function to remove neurotoxic waste products.

A metamaterial made of plastic and copper may be able to enhance the quality (signal-to-noise ratio) of magnetic resonance imaging (MRI) by four times and speed up scan times by 14 times.

Researchers have taken a key step forward in developing a new, possibly safer contrast agent for use in MRI exams.

Brain function can be tracked in real-time using a new MRI method that has the potential to shed light on altered neuronal activity in brain diseases.

A computer program using radiomic features found in routine MRI scans to distinguish between radiation necrosis and recurrent brain cancer has been developed.