Paper
14 August 2019 Neural classification of microscope digital pictures domestic pig oocytes
P. Boniecki, T. Kuzimska, S. Kujawa, W. Mueller, Ł. Gierz, K. Przybył, D. Wojcieszak, M. Zaborowicz, K. Koszela
Author Affiliations +
Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791E (2019) https://doi.org/10.1117/12.2539704
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
Abstract
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. The quality 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. In order to do that, the discriminative features of oocytes, presented in the digital photographs, were identified and extracted. This was necessary to create empirical training sets required in the process of generating neural classifiers.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P. Boniecki, T. Kuzimska, S. Kujawa, W. Mueller, Ł. Gierz, K. Przybył, D. Wojcieszak, M. Zaborowicz, and K. Koszela "Neural classification of microscope digital pictures domestic pig oocytes", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791E (14 August 2019); https://doi.org/10.1117/12.2539704
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image processing

Photography

Image analysis

Visualization

Neural networks

Statistical analysis

Error analysis

Back to Top