Automated Foot Radiograph Analysis – Study Results | July 2025

New Study Validates Milvue’s AI for Automated Foot Radiograph Analysis!

“Automatic Weight-Bearing Foot Series Measurements Using Deep Learning”, MDPI, by Jordan Tanzilli, Alexandre Parpaleix, Fabien de Oliveira, Mohamed Ali Chaouch, Maxime Tardieu, Malo Huard and Aymeric Guibal

We are thrilled to share a new peer-reviewed study published in the journal AI (MDPI), conducted by the research teams at Perpignan Hospital, France.

This publication provides an in-depth validation of Milvue’s deep learning solution for automating weight-bearing foot series measurements, a critical process for diagnosing conditions like hallux valgus.

The study’s key findings highlight the solution’s performance:

• Validated Accuracy: Milvue’s AI demonstrated excellent consistency with manual measurements performed by expert radiologists, achieving 94% accuracy in hallux valgus detection.
• Drastic Efficiency Gains: The AI provided a comprehensive analysis almost instantaneously, compared to an average of 203 seconds required for manual measurements per patient.

This research underscores our mission: to augment clinicians by automating time-consuming tasks. By enhancing workflows, Milvue helps free up practitioners to dedicate their invaluable expertise where it matters most—on patient care and complex decision-making.

A sincere thank you to the authors for their rigorous evaluation. This work is a testament to the powerful collaboration between clinical experts and artificial intelligence in shaping the future of medicine.

For a deep dive into the data, you can read the full study here: https://www.mdpi.com/2673-2688/6/7/144