Scanvio Medical provides an AI‑assisted ultrasound platform that gives real‑time feedback to gynecologists during transvaginal examinations for suspected endometriosis. The software highlights potential lesions, maps disease extent, and generates standardized reports to improve diagnostic confidence and treatment planning. It integrates as a software add‑on for existing ultrasound systems, enabling consistent, objective assessments across clinical settings.
Funding
$20K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
IFounders
Product
Problem
Endometriosis diagnosis is often delayed by 8-12 years due to the difficulty in detecting pathologies during standard ultrasound procedures. This lengthy delay results in prolonged suffering for patients, increased healthcare costs, and lost productivity.
Solution
Scanvio Medical offers the Scanvio AI Assistant, an AI-powered software designed to enhance transvaginal ultrasound examinations for more accurate endometriosis diagnosis. The software provides real-time feedback to guide gynecologists during the examination, improving the visualization of endometriosis-related pathologies. By offering comprehensive feedback on image quality, organ exposure, and probe orientation, the AI Assistant facilitates precise disease mapping and severity estimation. This leads to more reliable diagnoses, standardized reporting, and optimized patient management.
Target Audience
The primary target audience includes gynecologists, endometriosis centers, and ultrasound manufacturers seeking to improve the accuracy and efficiency of endometriosis diagnosis through AI-assisted ultrasound technology.
Features
- Real-time AI-driven feedback during transvaginal ultrasound examinations
- Enhanced visualization of endometriosis-related pathologies, including nodules and adhesions
- Standardized examination and reporting for consistent and objective assessments
- Guidance on image quality, organ exposure, and probe orientation
- Facilitation of precise disease mapping and severity estimation
- Integration into existing ultrasound platforms as a software add-on