In a pair of papers on retinal structure, Duke University neurobiologists have shown that the rigors of natural selection and evolution have shaped the retinas in our eyes just as this theory of optimization would predict.

Equipped with a color 3D camera, an inertial measurement sensor, and its own on-board computer, a newly improved robotic cane could offer blind and visually impaired users a new way to navigate indoors.

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.

Researchers at UCSD have developed a neural implant that monitors the activity of different parts of the brain at the same time, from the surface to deep structures.

Researchers at the University of Wisconsin have developed a micro-molded scaffolding photoreceptor “patch” designed to be implanted under a damaged or diseased retina.

Researchers at Keck School of Medicine of USC develop signals that could bring color vision and improved clarity to prosthesis for the blind.

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

While it isn’t surprising that infants and children love to look at people’s movements and faces, recent research from Rochester Institute of Technology studies exactly where they look when they see someone using sign language.

Training neural networks to perform tasks, such as recognizing images or navigating self-driving cars, could one day require less computing power and hardware thanks to a new artificial neuron device.

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.