Summary
The microscopic images of the cells are very difficult to analyze and to segment. The advanced method of segmentation such as region growing, watershed or snake requires the initialization information about the rough position of the cell body. It is proposed to localize cells in image using a threshold of simplified image. Clustering grey levels in image is proposed to simplify image. The k-means clustering method supported by weighting coefficients is chosen to collect all grey tones presented in the background into one cluster and other grey tones into few clusters in such a way that they cover a cell region in microscopic images. The weighting coefficients are used to influence (expand or contract) patterns in microscopic images of living cells. The method was evaluated on the basis of confocal and bright field microscopy images of cells in culture.
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Korzynska, A., Zdunczuk, M. (2008). Clustering as a Method of Image Simplification. In: Pietka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Advances in Soft Computing, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68168-7_39
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DOI: https://doi.org/10.1007/978-3-540-68168-7_39
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