SBIR/STTR Research Award

SBIR Phase I:Artificial intelligence (AI)-enabled ultrasound for imaging and diagnosing musculoskeletal injuries

Award identifier cf69f947ca7e124676c087814f17319680eb99da80b3cd252821a92bdfff8f87Awarding agency National Science Foundation

Award amount

$249,978

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Echo Mind Ai Corp
Proposal award date
2022-08-01
Contract end date
2023-07-31
UEI
L3ZDR67LXFZ1
Solicitation number
NSF 21-562
Topic code
DH

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable widespread adoption of ultrasound imaging for musculoskeletal (MSK) injuries. The ultrasound image analysis platform enabled by artificial intelligence (AI) developed during this SBIR may bring cost-effective diagnostic imaging to a broader patient population as the small form factor of the ultrasound instrument enables the technology to be used in a variety of settings, including doctors’ offices, physical therapy offices, and sports facilities. There are approximately 840,000 clinicians who see patients with MSK injuries. Each of these clinicians represents candidate customers for the platform, leading to a total addressable market in the U.S. of $1.7 billion.This Small Business Innovation Research (SBIR) Phase I project seeks to advance artificial intelligence (AI)-enabled ultrasound imaging technology. Sonography is the most operator-dependent medical imaging modality in use today, limiting the use of ultrasound imaging in musculoskeletal (MSK) evaluation. The proposed approach seeks to enable the wider adoption of ultrasound for diagnosing MSK injuries. This project involves the development of rigorous mathematical models to determine whether a frame sequence is properly aligned and determine if tendon tears in shoulder scans are diagnosable. A guidance system will be developed to aid in ultrasound probe placement so that consistent identification of tendon tear presence or absence is achieved. The proposed AI-enabled approach to ultrasound imaging and diagnostics may help practitioners position the ultrasound probe without the need to maintain precise angular positioning. Once at the correct starting position, the practitioner will move the probe in a pre-prescribed motion using a guidance system as needed for accurate and efficient image capture. The goal of the technology is to enable novice practitioners to capture relevant analyses to assist in providing a diagnosis and a treatment plan.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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

2 SBIR/STTR records share this UEI (2022–2025). Reported award amounts total $1,498,789. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

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