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Problem / Objective

India has one of the largest diabetic populations of any country in the world, approaching the alarming mark of 98 million cases by 2030. Diabetic Retinopathy (DR) is the major cause for blindness and vision loss in persons of working age. Hence, early detection and treatment are critical to stopping the damage. However, with majority of the population based in rural India, the lack of well-trained ophthalmologists to identify DR – especially in remote rural regions – is a major concern. Also, there remains a huge gap in the number of patients and the needed medical care and infrastructure available in the country.

Solution / Approach

To address this challenge, Sankara Eye Foundation collaborated with Leben Care to implement a cloud-based AI solution based on the Intel Xeon Scalable processor platform, powered by Intel Deep Learning Boost (Intel DL Boost). Netra.AI, a comprehensive retina risk assessment software-as-a-service platform available on cloud, has been trained to be device-agnostic to specialized low-powered microscopes with attached cameras. It provides the option to be used as both online and offline modules, such as a standalone box. The solution uses cutting- edge algorithms, developed in collaboration with leading retina experts, with a four-step deep convolutional neural network (DCNN). This neural network helps in detecting retinal photographs from non-retinal images, sensing generic quality distortion for automated image quality assessment, detecting the DR stage. It also helps in annotating the lesions based upon pixel density in the fundus images.  

Impact / Implementation

Netra.AI has the ability to identify healthy retina from an unhealthy one, which makes it a great tool to screen retinal disorders in a large population with limited infrastructure and resources for tertiary healthcare. The model is trained to identify different stages of diabetic retinopathy and suggest whether the patient may need an early referral or regular monitoring. Furthermore, it can identify glaucoma, which can be a great tool for early screening of this progressive disorder that leads to blindness, and thus help in early treatment and control. The comprehensive report generated by Netra.AI within 2 minutes of uploading the images enables optometrists or imaging technicians to provide instant counsel for patients needing a referral to the hospital. The solution also delivers excellent sensitivity and accuracy while detecting any DR, i.e., 99.7% and 98.5% respectively.

Sources of Case study

Source: Intel

Image from Flickr

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