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.
AI-Powered Software for Improving Accuracy in Prenatal Ultrasound Malformation Detection
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.
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.
What was built
A modular AI software platform featuring a 'Clinical Brain' that recognizes 1.6k anomalies and 450 syndromes to guide sonographers.
Who needs this
Who can put this to work
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.
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%.
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.
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.
Contact SONIO (France) via CORDIS portal
Talk to the team behind this work.
Contact us to explore licensing opportunities for the Clinical Brain AI.