Using artificial intelligence to improve the evaluation of human blastocyst morphology
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Data
2017-01-01
Autores
Rocha, José Celso [UNESP]
Da Silva, Diogo Lima Bezerra [UNESP]
Dos Santos, João Guilherme Cândido [UNESP]
Whyte, Lucy Benham
Hickman, Cristina
Lavery, Stuart
Nogueira, Marcelo Fábio Gouveia [UNESP]
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Resumo
The morphology of the human embryo produced by in vitro fertilized (IVF) is historically used as a predictive marker of gestational success. Although there are several different proposed methods to improve determination of embryo morphology, currently, all methods rely on a manual, optical and subjective evaluation done by an embryologist. Given that tiredness, mood and distinct experience could influence the accuracy of the evaluation, the results found are very different from embryologist to embryologist and from clinic to clinic. We propose the use of an objective evaluation, with repeatability and automatization, of the human blastocyst by image processing and the use of Artificial Neural Network (i.e., Artificial Intelligence).
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Artificial Intelligence, Embryo Classification, Human Embryo, Image Digital Processing
Como citar
IJCCI 2017 - Proceedings of the 9th International Joint Conference on Computational Intelligence, p. 354-359.