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EYENUK, INC. SBIR Phase II Award, September 2020

A SBIR Phase II contract was awarded to Eyenuk in September, 2020 for $1,000,000.0 USD from the U.S. Department of Health & Human Services and National Institutes of Health.

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sbir.gov/node/1915855
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Eyenuk
Eyenuk
0
Government Agency
0
Government Branch
National Institutes of Health
National Institutes of Health
0
Award Type
SBIR0
Contract Number (US Government)
2R44EY028081-020
Award Phase
Phase II0
Award Amount (USD)
1,000,0000
Date Awarded
September 1, 2020
0
End Date
August 31, 2023
0
Abstract

AbstractIn this grant application we propose to develop, EyeReadUWF, a fully automated tool for lesion characterization in ultra-widefield scanning laser ophthalmoscopy (UWF SLO) images. In recent times non mydriatic UWF SLO imaging has been shown to be a promising alternative to conventional digital color fundus imaging for grading of diabetic eye diseases, with advantages including 130°-200° field-of-view showing more than 80% of the retina in a single image, no need for multiple fields, multiple flashes, or refocusing between field acquisitions, ability to penetrate media opacities like cataract, and lower rate of ungradable images. UWF SLO images are particularly suitable for detecting predominantly peripheral lesions (PPLs), which have been associated with higher risk of diabetic retinopathy (DR) progression. Accurate quantification of presence and extent of PPLs can only be done by a robust automated tool that is specifically designed for the pseudo-colored images of UWF SLO modality. EyeReadUWF will automatically characterize lesions in pseudo colored UWF images while handling possible artifacts from eyelashes/eyelids and determine the lesion predominance in peripheral and central regions of UWF image. The ability to accurately quantify the presence and extent of predominantly peripheral lesions in UWF SLO images can enable clinicians to develop a more precise DR scoring scheme. This would help identify patients with higher risk of DR progression and onset of PDR, have a positive impact on diabetic patient management, and aid drug discovery research.Narrative The proposed tool, EyeReadUWF, will perform automated lesion characterization in ultra- widefield scanning laser ophthalmoscopy (UWF SLO) images to quantify the presence and extent of predominantly peripheral lesions (PPLs), which have been associated with higher risk of diabetic retinopathy (DR) progression. To the best of our knowledge, no commercial automated analysis tool is currently indicated for UWF SLO images. Once clinically validated, the tool can enable clinicians to triage patients with higher risk of DR progression and onset of PDR, have a positive impact on diabetic patient management, and aid drug discovery research.

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