Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology - Rocha, José Celso [UNESP]; Bezerra da Silva, Diogo Lima [UNESP]; Cândido Dos Santos, João Guilherme [UNESP]; Whyte, Lucy Benham; Hickman, Cristina; Lavery, Stuart; Gouveia Nogueira, Marcelo Fábio [UNESP] (INSTICC, 2017)
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).
Keywords: Artificial Intelligence; Embryo Classification; Human Embryo; Image Digital Processing