Communication Dans Un Congrès Année : 2024

Early prediction of the transferability of bovine embryos from videomicroscopy

Résumé

Videomicroscopy is a promising tool combined with machine learning for studying the early development of in vitro fertilized bovine embryos and assessing its transferability as soon as possible. We aim to predict the embryo transferability within four days at most, taking 2D time-lapse microscopy videos as input. We formulate this problem as a supervised binary classification problem for the classes transferable and not transferable. The challenges are three-fold: 1) poorly discriminating appearance and motion, 2) class ambiguity, 3) small amount of annotated data. We propose a 3D convolutional neural network involving three pathways, which makes it multi-scale in time and able to handle appearance and motion in different ways. For training, we retain the focal loss. Our model, named SFR, compares favorably to other methods. Experiments demonstrate its effectiveness and accuracy for our challenging biological task.
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hal-04880222 , version 1 (13-01-2025)

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  • HAL Id : hal-04880222 , version 1

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Yasmine Hachani, Patrick Bouthemy, Elisa Fromont, Sylvie Ruffini, Ludivine Laffont, et al.. Early prediction of the transferability of bovine embryos from videomicroscopy. ICIP 2024 - IEEE International Conference on Image Processing, Oct 2024, Abu DHABI, United Arab Emirates. pp.1-6. ⟨hal-04880222⟩
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