Delineating the heterogeneity of embryo preimplantation development using automated and accurate morphokinetic annotation

PURPOSE: Our objective was to design an automated deep learning model that extracts the morphokinetic events of embryos that were recorded by time-lapse incubators. Using automated annotation, we set out to characterize the temporal heterogeneity of preimplantation development across a large number...

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Detalles Bibliográficos
Autores principales: Zabari, Nir, Kan-Tor, Yoav, Or, Yuval, Shoham, Zeev, Shufaro, Yoel, Richter, Dganit, Har-Vardi, Iris, Ben-Meir, Assaf, Srebnik, Naama, Buxboim, Amnon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Assisted Reproduction Technologies
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310622/
https://www.ncbi.nlm.nih.gov/pubmed/37300648
http://dx.doi.org/10.1007/s10815-023-02806-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310622/
https://www.ncbi.nlm.nih.gov/pubmed/37300648
http://dx.doi.org/10.1007/s10815-023-02806-y

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