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Grantee News · September 17, 2020

Researchers have created a new PET imaging agent that detects signs of inflammation. Such a tracer could aid diagnosis and study of diseases ranging from cardiovascular disease to cancer to COVID-19.

NIBIB in the News · September 16, 2020

The NCI and the NIBIB chose the seven projects from nearly 200 different ideas. The projects represent a broad range of solutions for immediate public health needs related to the pandemic, and several focus on solutions for medically underserved communities and people with limited access to healthcare. Read more Health IT Analytics.

Press Releases · September 15, 2020

NIH has awarded seven contracts to companies and academic institutions to develop digital health solutions that help address the COVID-19 pandemic.

Press Releases · September 2, 2020

NIH announced $129.3 million in scale-up and manufacturing support for a new set of COVID-19 testing technologies as part of RADx. These tests add to initial awards made to seven companies on July 31, 2020.

Grantee News · August 31, 2020

Researchers have developed a groundbreaking process for multi-material 3D printing of lifelike models of the heart's aortic valve and the surrounding structures that mimic the exact look and feel of a real patient.

Grantee News · August 26, 2020

A new article looks at the use of virtual imaging trials in effective assessment and optimization of CT and radiography acquisitions and analysis tools to help manage the coronavirus disease (COVID-19) pandemic.

Press Releases · August 25, 2020

The winners of National Institutes of Health’s 9th annual Design by Biomedical Undergraduate Teams (DEBUT) challenge developed simple and low-cost diagnostics and treatments for conditions such as tuberculosis, cervical cancer, birth defects, and onchocerciasis (river blindness).

Grantee News · August 18, 2020

NIBIB-funded researchers at NYU Langone Health worked with Facebook AI researchers to develop a method to speed up MRI scans.

Grantee News · August 18, 2020

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