Neural analysis of bovine ovaries ultrasound images in the identification process of the corpus luteum: preliminary study

The aim of the paper is to present the neural image analysis as a method useful for identifying the position of the corpus luteum of domestic bovine on digital USG (UltraSonoGraphy) images. Corpus luteum is a transient endocrine gland that develops after ovulation from the follicle secretory cells. The main function of the corpus luteum is the production of progesterone, which regulates many reproductive functions. In the presented studies, identification of the corpus luteum was carried out on the basis of information contained in ultrasound digital images. Position of the corpus luteum was considered in two locations: on the surface of the ovary and within its parenchymal. Prior to the classification, the ultrasound images have been processed using a sharpening filter - unsharp mask. To generate a classification model, a Neural Networks module implemented in the STATISTICA was used. Five representative parameters describing the ultrasound image were used as learner variables. On the output of the artificial neural network was generated information about the location of the corpus luteum. Results of this study indicate that neural image analysis may be a useful instrument for identifying the bovine corpus luteum in the context of its location on the surface or in the ovarian parenchyma. Best-generated artificial neural network model was the structure of MLP (Multi Layer Perceptron) 5:5-364- 285-1:1.