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.
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