Automatic estrus cycle identification system on female dogs based on deep learning

Gustavo Calderón, Cesar Carrillo, Mariko Nakano, Jeanine Acevedo, José Ernesto Hernández

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Vaginal cytology is a complementary economic method and of simple realization, an indicative to determine in which stage of the estrous cycle the dog is, to achieve a higher fertility and fertility rate. This method is based on determining the type and quantity of cells of the different stages of the estrous cycle, since the hormonal changes that the vaginal mucosa undergoes during the estrous cycle are shown in the morphology of its epithelial cells. The canine female in her reproductive life goes through different phases of activity and hormonal rest that are repeated cyclically. This is called the estrous cycle and consists of 4 stages: proestrus, estrus, diestrus and anestrus. The interpretation of vaginal cytology’s, is a process to which a considerable amount of time is dedicated by its observation in the microscope and the same interpretation by the doctor which can become subjective and poorly performed, causing economic losses for the owners. Therefore, this work proposes an automatic system that will identify six types of cells and the quantity of them in the glass slide, based on a Faster R-CNN to determine in which stage of the estrous cycle the dog is. Our results show an accuracy of 91.6%. The proposed system will improve the efficiency and speed of cytology’s to decreased from 1 h approximately to just a few seconds.

Original languageEnglish
Title of host publicationPattern Recognition - 12th Mexican Conference, MCPR 2020, Proceedings
EditorsKarina Mariela Figueroa Mora, Juan Anzurez Marín, Jaime Cerda, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López
Number of pages8
ISBN (Print)9783030490751
StatePublished - 2020
Event12th Mexican Conference on Pattern Recognition, MCPR 2020 - Morelia, Mexico
Duration: 24 Jun 202027 Jun 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12088 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th Mexican Conference on Pattern Recognition, MCPR 2020


  • Cells
  • Deep learning
  • Estrous cycle
  • Faster R-CNN
  • Vaginal cytology


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