SBIR/STTR Research Award

Advanced Image Analysis Tools for Diabetic Retinopathy Telemedicine Applications

Award identifier da21f63afdd354ba603bad6eb7cf9cbc9210d9863be9c1449768246642694ad2Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$399,381

Program and phase

SBIR · Phase I

Award year

2012

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
EYENUK, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
ZCM5S7UD1WT4
Solicitation number
EB11-001
Topic code
NIBIB

Research abstract

DESCRIPTION (provided by applicant): Abstract In this small business innovations research (SBIR) project, we present aiArt: Advanced Image Analysis Tools for Diabetic Retinopathy Telemedicine applications. aiArt (pronounced eye-art), with its automated image analysis tools and user-friendly telemedicine web-interface, will enable exponential expansion of diabetic retinopathy screenings, thus fulfilling a significant health need as the number of people with diabetes climbs over the years. Latino population is genetically more prone to diabetes. Factors such as lack of awareness, lack of insurance coverage, and lack of access to expert clinicians greatly increase this disparity population's vulnerability to blindness due to DR. The situation is particularly grim in Los Angeles County, where there is a backlog of several thousand patients waiting to see an ophthalmologist, causing very long appointment wait times (often over six months). To help reduce risk of vision loss in this population, we propose to use advanced image analysis algorithms in conjunction with existing telemedicine initiatives to enable faster screening, allow reprioritization of ophthalmologist appointments, and to provide patient education tools. Our automated image analysis algorithms represent cutting-edge of research in image processing, computer vision, and machine learning. The analysis engine will be closely integrated with simple, easy-to-use web-based telemedicine infrastructure provided by an existing, popular, telemedicine initiative, EyePACS. PUBLIC HEALTH RELEVANCE: Narrative The proposed image analysis tools will greatly reduce the cost of diabetic retinopathy screening, and with its web and mobile phone accessible interface will drive an expansion of diabetic retinopathy screening, making it accessible to disparity populations (such as Latinos) which are not currently being screened due to socio-economic factors. The proposed tools will also enable quick turnaround time for screening, thus further helping prevent blindness due to diabetes complications.

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

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.