Classification of the estrous cycle through texture and shape features

We show, for the first time, an autonomous classification of the estrous cycle (the reproductive cycle in rats), This cycle consists of 4 stages: Proestrus, Estrus, Metestrus and Diestrus. The short duration of the cycle in rats makes them an ideal model for research about changes that occur during the reproductive cycle. Classification is based on the cytology shown by vaginal smear. For this reason, we used texture and shape features on the gray level color space and CIELAB color space on channels A and B, which were classified using support vector machines (SVM) and the artificial neural network multilayer perceptron (MLP). As dataset of 412 images of estrous cycle was used. It was divided into two sets. The first contains all four stages, the second contains two classes. The first class is formed by the stages Proestrus and Estrous and the second class is formed by the stages Metestrus and Diestrus. The two sets were formed to solve the main problems, the research of the reproductive cycle and the reproduction control of rodents. For the first set, we obtained an 87% of validation accuracy and 100% of validation accuracy for the second set using the multilayer perceptron. The results were validated through cross validation using 5 sets and F₁ metric.