Kavya Kopparapu, a 16 year old student at Thomas Jefferson High School for Science and Technology, Virginia, has invented a 3D printed device that can detect signs of degenerative eye disease.

The device works with an AI smartphone app. Kopparapu and her team digitally trained the Eyeagnosis package which is intended to be a cheaper, more accessible eye care alternative for patients with diabetes.

One third of the 415 million diabetics worldwide will develop diabetic retinopathy. Image via the NIH National Eye Institute

 

One third of the 415 million diabetics worldwide will develop diabetic retinopathy in their life time. Image via the NIH National Eye Institute

A fast-acting diagnosis to prevent blindness

Development of Eyeagnosis started when Kopparapu’s grandfather began exhibiting symptoms of diabetic retinopathy in his eye.

The disease, which affects around one third of diabetics worldwide, causes degeneration of blood vessels in the retina. If untreated severe cases can also cause blindness.

Kopparapu's Eyeagnosis app and 3D printed device can spot the telltale sign of diabetic retinopathy of the eye. Image via Wiles Eye Center, Perfect2020

 

Kopparapu’s Eyeagnosis app and 3D printed device can spot the telltale sign of diabetic retinopathy of the eye. Image via Wiles Eye Center, Perfect2020

Looking for a solution to provide fast-acting diagnosis with bare-minimum equipment, Kopparapu, her 15-year-old brother Neeyanth, and high school classmate Justin Zhang, decided to put their computer science knowledge to the test.

Teaching smartphones to read the retina

The 3D printed device created by the team is a frame designed to fit comfortably on the back of a typical smartphone.

With a lens to focus the light from a phone camera’s flash, the device works the same as an eye-doctor’s pen torch –  illuminating the retina at the back of the eye.

Kopparapu's Eyeagnosis system. Photo by Kavya Kopparapu

 

Kopparapu’s Eyeagnosis system. Photo by Kavya Kopparapu

A photo is taken of the retina, and it is run through the Eyeagnosis app.

The app was trained to detect symptoms by Kopparapu and her team using image data from the NIH National Eye Institute’s eyeGENE database.

The finished device has since been tested by Aditya Jyot Eye Hospital in Mumbai that proved the package is able to diagnose with accuracy of a human ophthalmologist.

 

Article content, images are appeared from 3DPrintingIndustry and 

 
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