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Computer Recognition Systems 2 pp 604–612Cite as

Automatic Counting of Neural Stem Cells Growing in Cultures

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Part of the book series: Advances in Soft Computing ((AINSC,volume 45))

Abstract

Stem cells are a potential source of cells for use in the regenerative medicine. Automation of monitoring and analysis is crucial for reliable and fast optimization of culturing methods. The goal of the first step in this investigation is to find a method of automatic cell counting on microscopic static images. In our method, an image is divided into two types of regions: the regions covered by cells and the background regions. Next the cell regions are classified into three categories: converged cells,the flatten cells and the transitional cells regions. For each type of region, the adjusted procedure estimates a quantity of cells. The quantity of cells in image has been obtained for randomly chosen images from certain sequences captured from cells which growth has been monitored using laser scanner confocal microscopy. The results of the automatic cell counting are compared with results obtained by an operator and the difference has been admissible. When a lot of frames and cells are counted, the accuracy of the proposed method has been similar to the accuracy of an expert.

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Author information

Authors and Affiliations

  1. Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, ul. Ksiecia Trojdena 4, 02-109, Warszawa, Poland

    Anna Korzynska

Authors
  1. Anna Korzynska
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Editor information

Editors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzynski , Edward Puchala , Michal Wozniak  & Andrzej Zolnierek , ,  & 

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© 2007 Springer-Verlag Berlin Heidelberg

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Korzynska, A. (2007). Automatic Counting of Neural Stem Cells Growing in Cultures. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_76

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  • DOI: https://doi.org/10.1007/978-3-540-75175-5_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75174-8

  • Online ISBN: 978-3-540-75175-5

  • eBook Packages: EngineeringEngineering (R0)

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