SciTransfer
d3pm · Project

AI-Powered Software for Improving Accuracy in Prenatal Ultrasound Malformation Detection

healthPilotedTRL 7

Imagine a smart assistant for doctors that acts like a high-tech checklist during pregnancy scans. It helps them spot rare physical abnormalities in babies that are often missed because the exams are so complex. By guiding the doctor's hand and analyzing images in real-time, it ensures no critical detail is overlooked.

By the numbers
50%
Congenital malformations not detected antenatally
1.6k
Anomalies the Clinical Brain is aware of
49% to 97%
Improvement in exam pass rates using checklists
2.7%
Foetuses with at least one congenital malformation
The business problem

What needed solving

Prenatal ultrasound is highly operator-dependent, leading to 50% of congenital malformations going undetected. Current manual checklists are too cumbersome for doctors to use in practice.

The solution

What was built

A modular AI software platform featuring a 'Clinical Brain' that recognizes 1.6k anomalies and 450 syndromes to guide sonographers.

Audience

Who needs this

OBGYN clinicsFetal medicine specialistsUltrasound equipment manufacturersPublic health systems
Business applications

Who can put this to work

Medical Software
SME
Target: Health-tech software developers

If you are a software developer dealing with the high complexity of fetal imaging — this project developed a modular platform that integrates image recognition and genomics to identify 1.6k anomalies.

Healthcare Providers
mid-size
Target: Private prenatal clinics

If you are a clinic owner dealing with high operator-dependency and missed diagnoses — this project developed a Clinical Brain that can prioritize anomalies to identify the most probable diagnoses.

Medical Device Manufacturing
enterprise
Target: Ultrasound machine manufacturers

If you are a manufacturer dealing with the limit of clinical expertise in ultrasound use — this project developed AI software that can automate checklists, potentially improving exam pass rates from 49% to 97%.

Frequently asked

Quick answers

What is the cost or pricing model for this software?

Based on available project data, specific pricing or cost structures are not provided.

Can this be scaled to an industrial level?

The project is designed as a modular software platform capable of guiding OBGYNs and sonographers worldwide, suggesting high scalability potential.

What is the IP or licensing status?

Based on available project data, specific patent or licensing details are not mentioned, though it is developed by an SME (SONIO).

How does this integrate with existing hospital workflows?

It acts as a modular software platform that guides practitioners during the ultrasound exam, replacing cumbersome manual checklists with AI-driven guidance.

What is the timeline for deployment?

The project period was from 2023-01-01 to 2024-12-31.

Consortium

Who built it

The project is led by a single French SME, SONIO, with a 100% industry ratio. This lean structure suggests a highly commercial focus and rapid decision-making, utilizing a EUR 2,500,000 EU contribution to move from a specialized clinical brain to a full-scale AI diagnostic platform.

How to reach the team

Contact SONIO (France) via CORDIS portal

Next steps

Talk to the team behind this work.

Contact us to explore licensing opportunities for the Clinical Brain AI.

More in Health & Biomedical
See all Health & Biomedical projects