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A Neural Network-Based Identification of Developmentally Competent or Incompetent Mouse Fully-Grown Oocytes
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1Laboratorio di Biologia dello Sviluppo, Dipartimento di Biologia e Biotecnologie “Lazzaro Spallanzani”,University of Pavia, 2Institute of Biotechnology,University of Helsinki, 3Department of Reproductive Medicine,University of California San Diego, 4Dipartimento di Ingegneria Industriale e dell’Informazione,University of Pavia
Chapters
- 00:00Title
- 00:14Introduction
- 02:03Cumulus Oocyte Complex isolation
- 03:25Oocyte classification with fluorochrome Hoechst 33342
- 04:56Neural network-based oocyte classification
- 06:12Results
- 09:38Conclusion
Here, we present a protocol for non-invasive assessment of oocyte developmental competence performed during their in vitro maturation from the germinal vesicle to the metaphase II stage. This method combines time-lapse imaging with particle image velocimetry (PIV) and neural network analyses.
