Point-of-care system can capture high-resolution images inside the eye

A new point-of-care system can image a patient's eye to help monitor eye health and spot signs of macular degeneration and diabetic retinopathy.

Mar 18th, 2015
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Researchers at Rice University (Houston, TX) developed a point-of-care system that can image a patient's eye to help monitor eye health and spot signs of macular degeneration and diabetic retinopathy, especially in developing nations.

Called mobileVision, the patient-operated, portable device can be paired with a smartphone to give clinicians finely detailed images of the macula, the spot in the center of the eye where vision is sharpest, without artificially dilating the pupil. Those images are then sent by cellphone to ophthalmologists who can make their diagnoses from afar.

The eye is the body's only portal that allows direct, noninvasive imaging of internal tissue like blood vessels, according to the researchers. A number of labs are taking advantage of cellphones' increasingly sophisticated cameras to put diagnostic tools in the field, and the Rice researchers believe they are leading the charge with a device patients can use on their own with minimal instruction.

Generally, doctors have to dilate a patient's eyes before an exam, which often involves bulky, expensive equipment. The challenge for the Rice engineers, explains Ashok Veeraraghavan, an assistant professor of electrical and computer engineering, was to produce a portable device that provides high-quality images of the macula without dilation.

"Whatever you look directly at you see in very high resolution, while your peripheral vision is blurry," Veeraraghavan says. "The region of the retina that provides you with this high resolution is the macula. And degradation of the macula immediately affects your eyesight."

Rice University research engineer Adam Samaniego demonstrates mobileVision, a device to image the retina without having to dilate a patient's eye. The device will allow patients to quickly capture images of their own retinas for later analysis by doctors. (Image credit: Jeff Fitlow/Rice University)

The result of three years of research and prototyping is a device that looks and works something like a reverse microscope. A patient looks into the eyepiece and sees a large, dark-red disk. When the system is shifted around freely, the appearance of the disk changes dramatically—appearing brightest and most uniform when perfectly aligned with the patient's eye. When this happens, the patient hits a button that moves the target out of the way and allows the camera to see into the eye, with help from a battery-powered light source.

"That dark target induces pupil dilation naturally," says Adam Samaniego, a Rice alumnus and research engineer. "When you present the eye with a stimulus that isn't throwing a lot of photons at it, the eye dilates to collect more light and have a better look." When the patient can clearly see the disk, the pupil is dilated and the system is aligned, he says.


Once the retina is illuminated, Samaniego says, "We have a window of only a few hundred milliseconds to snap as many frames as we can before the pupil constricts again."

At that point, the patient's job is done. In an ideal situation, Samaniego says, a mobile clinic anywhere in the world could use multiple mobileVision systems to gather data from many patients very quickly. "There might be one individual who's telling a number of people how to do different tests with different devices," he says.

A retinal image taken with the mobileVision platform invented at Rice University. (Image credit: Adam Samaniego/Rice University)

In the researchers' lab, mobileVision is connected to a small camera and tied to a computer. But in the field, a cellphone would capture video and break it down into a series of still images that can be analyzed and enhanced through a computational technique known as "lucky imaging."

"This technique was invented for astronomers who image stars from Earth and have to correct for the effects of atmospheric turbulence that cause a loss in resolution," Veeraraghavan says.

"The naïve thing to do is take hundreds of images and use the best one. You would feel lucky if you found something that looked good," he says. Instead, the Rice algorithm takes a sampling of the many images captured before the pupil closes and fuses them to enhance the features.

While they refine their device, the research team has also been participating in a National Science Foundation program called Innovation Corps (or I-Corps) that helps researchers prepare their basic research for use beyond the lab.

The team presented the first comprehensive results of their work at the Wireless Health 2014 conference in Bethesda, MD, in October 2014.

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