Combined Input Deep Learning Pipeline for Embryo Selection for In Vitro Fertilization Using Light Microscopic Images and Additional Features

Combined Input Deep Learning Pipeline for Embryo Selection for In Vitro Fertilization Using Light Microscopic Images and Additional Features

The current process of embryo selection in in vitro fertilization is based on morphological criteria; embryos are manually evaluated by embryologists under subjective assessment. In this study, a deep learning-based pipeline was developed to classify the viability of embryos using combined inputs, i...

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Bibliographic Details
Main Authors: Krittapat Onthuam, Norrawee Charnpinyo, Kornrapee Suthicharoenpanich, Supphaset Engphaiboon, Punnarai Siricharoen, Ronnapee Chaichaowarat, Chanakarn Suebthawinkul
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Journal of Imaging
Subjects:
deep learning
embryo image
embryo morphology
CNNs
GANs
in vitro fertilization
Online Access:https://www.mdpi.com/2313-433X/11/1/13
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