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Nicolas Sananes – Deep Learning for Fetal Biometries
Nicolas Sananès/LinkedIn
Oct 8, 2025, 13:30

Nicolas Sananes – Deep Learning for Fetal Biometries

Nicolas Sananes, Professor of Obstetrics and Gynecology at American Hospital of Paris, shared a post on LinkedIn about a paper by Morgane Goetz-Fu et al. published in the Journal of Gynecology Obstetrics and Human Reproduction:

“I share here an article on an automated measurement of fetal biometrics by Artificial Intelligence, published in the Journal of Gynecology Obstetrics and Human Reproduction, following a work in collaboration with IRCAD.

We were able to develop a deep neural network algorithm that detects in real time the appropriate cutting planes and makes an automated measurement of fetal biometrics.

A big thank you and congratulations to Morgane Goetz-Fu, to the IRCAD team (Alexandre Hostettler, Mathieu Haller, Toby Collins, Josiane Uwinesa, Yvonne Keeza and Jacques Marescaux), as well as to Nathan Begusic, Floriane Jochum and Anne Sophie Weingertner.

Beyond the scientific work, it is also a stimulating adventure with the IRCAD R&D team.”

Title: Development and temporal validation of a deep learning model for automatic fetal biometry from ultrasound videos

Authors: M. Goetz-Fu, M. Haller, T. Collins, N. Begusic, F. Jochum, Y. Keeza, J. Uwineza, J. Marescaux, A.S. Weingertner, N. Sananès, A. Hostettler

Read the full article.

Nicolas Sananès

Alexandre Hostettler Anne Sophie Weingertner Artificial Intelligence Fertility Fertility News fetal biometrics Floriane Jochum Gynecology Obstetrics and Human Reproduction IRCAD Jacques Marescaux Josiane Uwinesa Journal of Gynecology Obstetrics and Human Reproduction Mathieu Haller Morgane GOETZ-FU Nathan Begusic Toby Collins Yvonne Keeza
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