Software based on Artificial Neural Networks for embryo morphologic evaluation

• Grant number: 12/20110-2
• Support Opportunities: Scholarships in Brazil - Master
• Start date: June 01, 2013
• End date: July 31, 2014
• Field of knowledge: Biological Sciences - Morphology - Embryology
• Principal Investigator: Marcelo Fábio Gouveia Nogueira
• Grantee: Felipe Delestro Matos
• Host Institution: Faculdade de Ciências e Letras (FCL-ASSIS). Universidade Estadual Paulista (UNESP). Campus de Assis. Assis , SP, Brazil

Abstract

The morphologic embrionary classification has great importance for innumerous laboratorial techniques (from basic research to applied on assisted reproduction). Nevertheless, the current method for classification of embryos in different degrees of quality is always based on the subjectivity of the evaluator and, even that standard degrees of quality and descriptions of the morphologic characteristics that categorize an embryo in certain degree have been made, there is no precise method that can generate results that have consistency and are trustworthy. This way, with this project we will to develop a software that is capable to realize the morphologic embryo classification for cattle and humans. We will make use of techniques of artificial intelligence (such as Artificial Neural Networks) and digital image processing. The final product will be a software with a friendly user interface, that can be used by scholars in the field of embryology and technicians, only been needed a basic knowledge of embryology.

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ROCHA, JOSE CELSO; PASSALIA, FELIPE JOSE; MATOS, FELIPE DELESTRO; TAKAHASHI, MARIA BEATRIZ; MASERATI, JR., MARC PETER; ALVES, MAYRA FERNANDA; DE ALMEIDA, TAMIE GUIBU; CARDOSO, BRUNA LOPES; BASSO, ANDREA CRISTINA; GOUVEIA NOGUEIRA, MARCELO FABIO. Automatized image processing of bovine blastocysts produced in vitro for quantitative variable determination. SCIENTIFIC DATA, v. 4, DEC 19 2017. (16/19004-4, 11/06179-7, 06/06491-2, 13/05083-1, 12/50533-2, 12/20110-2)

ROCHA, JOSE CELSO; PASSALIA, FELIPE JOSE; MATOS, FELIPE DELESTRO; TAKAHASHI, MARIA BEATRIZ; CINICIATO, DIEGO DE SOUZA; MASERATI, MARC PETER; ALVES, MAYRA FERNANDA; DE ALMEIDA, TAMIE GUIBU; CARDOSO, BRUNA LOPES; BASSO, ANDREA CRISTINA; et al. A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images. SCIENTIFIC REPORTS, v. 7, AUG 9 2017. (11/06179-7, 06/06491-2, 13/05083-1, 12/50533-2, 12/20110-2)

ROCHA, J. C.; MATOS, F. D.; BASSO, A. C.; HICKMAN, C. F. L.; LAVERY, S.; NOGUEIRA, M. F. G.. Using artificial intelligence to improve blastocyst morphology evaluation. Human Reproduction, v. 32, p. 2-pg., 2017-07-01. (12/50533-2, 06/06491-2, 13/05083-1, 12/20110-2)

ROCHA, JOSE C.; PASSALIA, FELIPE; MATOS, FELIPE D.; MASERATI, JR., MARC P.; ALVES, MAYRA F.; DE ALMEIDA, TAMIE G.; CARDOSO, BRUNA L.; BASSO, ANDREA C.; NOGUEIRA, MARCELO F. G.. Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?. JORNAL BRASILEIRO DE REPRODUCAO ASSISTIDA, v. 20, n. 3, p. 150-158, JUL-SEP 2016. (12/50533-2, 12/20110-2, 06/06491-2, 11/06179-7)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

MATOS, Felipe Delestro. Software baseado em rede neural artificial desenvolvido por meio de algoritmo genético para a classificação morfológica de blastocistos bovinos. 2014. Master's Dissertation - Universidade Estadual Paulista (Unesp). Faculdade de Ciências e Letras. Assis Assis.