SBIR/STTR Research Award

Automated end-to-end retinal screening system with robotic image capture and deep learning analysis

Award identifier abfb6b842b0b823310e64de86c34030e1f92c633d97022d333ca6f9e9f7c4dcdAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$218,618

Program and phase

SBIR · Phase I

Award year

2019

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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
2019-09-30
Contract end date
2020-09-29
UEI
ZCM5S7UD1WT4
Solicitation number
PA18-574
Topic code
NEI

Research abstract

AbstractIn this SBIR projectwe propose EyeScreenBotan end to end automated retinal image capture and analysis systemcomprising a self drivenrobotic fundus camera platform for automated image capture and a deep learning based image analysis engine for generation of automated screening outcomeWith the largegrowingand aging population and the increased prevalence of diabetesa large number of people are at risk for vision loss due to several eye diseases including diabetic retinopathyDRage related macular degenerationAMDand glaucomaAlthough eye screening is effective in reducing vision lossthere are not enough clinical personnel and eye care experts for population wide eye screeningRecent advances with automated image analysis are helping alleviate the situationbut they are still limited by the need for good quality images of the patients captured by trained technicians or expensive retinal cameras equipped for automated captureEyeScreenBot will be developed to provide a truly end to end screening solution that is cost effective and suitable for deployment in primary care clinics or optometrist sitesaddressing both automated capture and subsequent automated analysisall without the need for trained technicians or eye experts at the point of careWhen deployed and commercializedthis device will rapidly aid scaling of eye screening for the massesthereby having an enormous impact in improving the quality and accessibility of eye care and helping reduce preventable vision loss Narrative EyeScreenBotan end to end automated screening system with intelligent image capture and analysiswill truly enable eye screening at massive scalewhich is necessary and urgent since the population at risk for preventable vision loss due to retinal diseasessuch as diabetic retinopathyis growing at a staggering rateTriaging and identification of at risk patients will allow for timely intervention to preventslowor even reverse the disease progression and loss of vision

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

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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