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Neural classification of microscope digital pictures domestic pig oocytes
Author(s): P. Boniecki; T. Kuzimska; S. Kujawa; W. Mueller; Ł. Gierz; K. Przybył; D. Wojcieszak; M. Zaborowicz; K. Koszela
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Paper 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.

Paper Details

Date Published: 14 August 2019
PDF: 8 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791E (14 August 2019); doi: 10.1117/12.2539704
Show Author Affiliations
P. Boniecki, Poznan Univ. of Life Sciences (Poland)
T. Kuzimska, Poznan Univ. of Life Sciences (Poland)
S. Kujawa, Poznan Univ. of Life Sciences (Poland)
W. Mueller, Poznan Univ. of Life Sciences (Poland)
Ł. Gierz, Poznan Univ. of Technology (Poland)
K. Przybył, Poznan Univ. of Life Sciences (Poland)
D. Wojcieszak, Poznan Univ. of Life Sciences (Poland)
M. Zaborowicz, Poznan Univ. of Life Sciences (Poland)
K. Koszela, Poznan Univ. of Life Sciences (Poland)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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