Evaluation of deep convolutional neural networks in classifying human embryo images based on their morphological quality

Evaluation of deep convolutional neural networks in classifying human embryo images based on their morphological quality

A critical factor that influences the success of an in-vitro fertilization (IVF) treatment cycle is the quality of the transferred embryo. Embryo morphology assessments, conventionally performed through manual microscopic analysis suffer from disparities in practice, selection criteria, and subjecti...

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Bibliographic Details
Main Authors: Prudhvi Thirumalaraju, Manoj Kumar Kanakasabapathy, Charles L. Bormann, Raghav Gupta, Rohan Pooniwala, Hemanth Kandula, Irene Souter, Irene Dimitriadis, Hadi Shafiee
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:Heliyon
Subjects:
Deep neural networks
Convolutional neural networks
Human embryos
In-vitro fertilization
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844021004035

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http://www.sciencedirect.com/science/article/pii/S2405844021004035

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