Oocyte classification with fluorochrome Hoechst 33342
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Neural network-based oocyte classification
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Results
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Conclusion
Transcribir
The overall goal of this procedure is the identification of occytes with a backside developmental capacity using a non-invasive tool. The main advantage of this method is that by simply observing the oocyte movements occurring during in vitro matu
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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.