Inżynieria Rolnicza
Home page
Place of Work
Title : The use of neural image analysis in the identification of information encoded in a graphical form
Key words : identification of class oocytes, quality classification, computer image analysis image analysis, artificial neural networks
Summary :

Numerous scientific and research centres are searching for solutions concerning the problem of quality classification of animal oocytes. Conducting such studies is purposeful, particularly in the context of constant attempts to improve the quality of food products, which depends on the breeding value of livestock. Therefore, searching for methods of stimulation of proper development of a larger number of animal oocytes, particularly in extracorporeal conditions, gains special importance. An increasing interest in assisted reproduction techniques resulted in searching for new, increasingly effective methods of quality assessment of mammalian gametes and embryos. The expected progress in the production of animal embryos in vitro is largely dependent on proper classification of obtained oocytes. The aim of this work was to develop a non-invasive method for the quality assessment of oocytes, performed on the basis of graphic information encoded in the form of monochromatic digital images obtained via microscopy techniques. The classification process was conducted based on the information presented in the form of microphotography pictures of domestic pig oocytes, using advanced methods of neural image analysis.

Please use the following format to cite the selected article : Koszela, K., Boniecki, P., Kuzimska, T. (2015). The use of neural image analysis in the identification of information encoded in a graphical form. Inzynieria Rolnicza, 3(155), 25-35.
Download :
Current affiliation
If you see any errors, please contact: Redakcja PTIR