NEI Research News

Four teams have won a prize competition aimed at integrating eye care and ocular imaging data into studies using large healthcare datasets in biomedical research.

Scientists at the National Institutes of Health (NIH) have leveraged artificial intelligence to transform a device designed to see tissues in the back of the eye into one sharp enough to make out individual cells.

Researchers used an imaging technology called adaptive optics to identify rare cells that could help fill in the gaps in existing theories of color perception.

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is 100 times faster and improves image contrast 3.5-fold.

Researchers have found that in dogs, fMRI can detect brain responses to daylight vision for black and white information as well as color information, and identify the area of the visual cortex that responds to stimulation of a cone-rich retinal region.

Researchers combined retinal imaging, genetics and big data to estimate how likely a person is to develop eye and systemic diseases in the future.

The NEI and partners have published an editorial on the value of being able to store and share eye imaging data in standard formats.

Research funded by the National Eye Institute suggests that low density of pigment in the macula, the region of the retina required for sharp central vision, is associated with thinning of the retina and may serve as an early warning sign of glaucoma.

David Williams, Donald Miller, and Austin Roorda, received recognition for the development of instruments that use adaptive optics technologies to capture high-resolution images of the retina.

All of Us is assembling a large-cohort dataset of at least 1 million participants who reflect the diversity of the U.S. population.