TY - GEN
T1 - Automatic estrus cycle identification system on female dogs based on deep learning
AU - Calderón, Gustavo
AU - Carrillo, Cesar
AU - Nakano, Mariko
AU - Acevedo, Jeanine
AU - Hernández, José Ernesto
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Cells
KW - Deep learning
KW - Estrous cycle
KW - Faster R-CNN
KW - Vaginal cytology
UR - http://www.scopus.com/inward/record.url?scp=85087284910&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-49076-8_25
DO - 10.1007/978-3-030-49076-8_25
M3 - Contribución a la conferencia
AN - SCOPUS:85087284910
SN - 9783030490751
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 261
EP - 268
BT - Pattern Recognition - 12th Mexican Conference, MCPR 2020, Proceedings
A2 - Figueroa Mora, Karina Mariela
A2 - Anzurez Marín, Juan
A2 - Cerda, Jaime
A2 - Carrasco-Ochoa, Jesús Ariel
A2 - Martínez-Trinidad, José Francisco
A2 - Olvera-López, José Arturo
PB - Springer
T2 - 12th Mexican Conference on Pattern Recognition, MCPR 2020
Y2 - 24 June 2020 through 27 June 2020
ER -