SBIR/STTR Research Award

Fully-automated lesion characterization in ultrawide-field retinal images

Award identifier c866f7d142fd644b21f2c6a00b0fa0bd2fef61497207e1cfe2d612892886f9d4Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$216,440

Program and phase

SBIR · Phase I

Award year

2018

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
EYENUK, INC.
Proposal award date
2018-06-01
Contract end date
2019-05-31
UEI
ZCM5S7UD1WT4
Solicitation number
PA17-302
Topic code
N

Research abstract

AbstractIn this grant application we propose to developEyeReadUWFa fully automated tool for lesion characterization in ultra widefield scanning laser ophthalmoscopyUWF SLOimagesIn 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 diseaseswith advantages includingfield of view showing more thanof the retina in a single imageno need for multiple fieldsmultiple flashesor refocusing between field acquisitionsability to penetrate media opacities like cataractand lower rate of ungradable imagesUWF SLO images are particularly suitable for detecting predominantly peripheral lesionsPPLswhich have been associated with higher risk of diabetic retinopathyDRprogressionAccurate 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 modalityEyeReadUWF will automatically characterize lesions in pseudo colored UWF images while handling possible artifacts from eyelashes and determine the lesion predominance in peripheral and central regions of UWF imageThe ability to accurately quantify the presence and extent of predominantly peripheral lesions in UWF SLO images can enable clinicians to triage patients with higher risk of DR progression and onset of PDRhave a positive impact on diabetic patient managementand aid drug discovery research Narrative The proposed toolEyeReadUWFwill perform automated lesion characterization in ultrawidefield scanning laser ophthalmoscopyUWF SLOimages to quantify the presence and extent of predominantly peripheral lesionsPPLswhich have been associated with higher risk of diabetic retinopathyDRprogressionTo the best of our knowledgeno commercial automated analysis tool is currently indicated for UWF SLO imagesOnce clinically validatedthe tool can enable clinicians to triage patients with higher risk of DR progression and onset of PDRhave a positive impact on diabetic patient managementand aid drug discovery research

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

13 SBIR/STTR records share this UEI (2012–2020). Reported award amounts total $9,832,543. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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