An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization

An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization

Abstract Medical Assisted Reproduction proved its efficacy to treat the vast majority forms of infertility. One of the key procedures in this treatment is the selection and transfer of the embryo with the highest developmental potential. To assess this potential, clinical embryologists routinely wor...

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Bibliographic Details
Main Authors: Florian Kromp, Raphael Wagner, Basak Balaban, Véronique Cottin, Irene Cuevas-Saiz, Clara Schachner, Peter Fancsovits, Mohamed Fawzy, Lukas Fischer, Necati Findikli, Borut Kovačič, Dejan Ljiljak, Iris Martínez-Rodero, Lodovico Parmegiani, Omar Shebl, Xie Min, Thomas Ebner
Format: Article
Language:English
Published: Nature Portfolio 2023-05-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-023-02182-3

Internet

https://doi.org/10.1038/s41597-023-02182-3

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