New biomarkers found in the eyes could unlock the key to helping manage diabetic retinopathy, and perhaps even diabetes, according to new research conducted at the Indiana University School of Optometry.

A National Eye Institute-funded project at Duke University has yielded a fully automated optical coherence tomography (OCT) device that does not require a trained operator and promises to broaden access to retinal imaging technology.

Tiarnan Keenan, NEI Division of Epidemiology and Clinical Applications, and colleagues found that people with age-related macular degeneration (AMD) can successfully use the Notal Home OCT device to monitor their disease.

A new combination of optical coherence tomography (OCT), adaptive optics and deep neural networks should enable better diagnosis and monitoring for neuron-damaging eye and brain diseases like glaucoma.

As regenerative therapies for blinding diseases move closer to clinical trials, the NEI's functional imaging consortium is pioneering noninvasive technologies to monitor the function of the retina’s neurons and their connections to the brain.

Not all health care providers speak the same language, but the software in their clinical imaging devices can and should.

A team led by scientists at the National Eye Institute (NEI) has noninvasively visualized the light-sensing cells in the back of the eye, known as photoreceptors, in greater detail than ever before.

Researchers from UW Medicine have found that artificial intelligence-based screening algorithms to diagnose diabetic retinopathy do not perform as well as they claim.

Scientists at Joslin Diabetes Center now have shown that routine eye imaging can identify changes in the retina that may be associated with cognitive disorders in older people with type 1 diabetes.

The IQA is a software system intended for use in importing, displaying, analyzing and managing images acquired with digital fundus cameras. The patented software detects the most common causes of retinal imaging artifacts.