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We describe the steps of our machine learning pipeline to phenotype oocyte based on images/movies acquired noninvasively in transmitted light. The pipeline allows to extract hundreds of morphological/dynamical features describing individual oocytes by segmenting the oocyte contours and measuring the corresponding features. Oocytes are then characterized by running feature-based machine learning algorithm on the features.

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Machine Learning Methods to Characterize Mouse and Human Oocytes

  • 实验方案

  • 发表日期：

    2025年

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  • Gaëlle Letort

摘要

We describe the steps of our machine learning pipeline to phenotype oocyte based on images/movies acquired noninvasively in transmitted light. The pipeline allows to extract hundreds of morphological/dynamical features describing individual oocytes by segmenting the oocyte contours and measuring the corresponding features. Oocytes are then characterized by running feature-based machine learning algorithm on the features.