Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images

Tscherepanow M, Zöllner F, Hillebrand M, Kummert F (2008)
In: Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA). Perner P, Salvetti O (Eds); Berlin: Springer: 158-172.

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Konferenzbeitrag | Veröffentlicht | Englisch
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Abstract / Bemerkung
The automatic subcellular localisation of proteins in living cells is a critical step in determining their function. The evaluation of fluorescence images constitutes a common method of localising these proteins. For this, additional knowledge about the position of the considered cells within an image is required. In an automated system, it is advantageous to recognise these cells in bright-field microscope images taken in parallel with the regarded fluorescence micrographs. Unfortunately, currently available cell recognition methods are only of limited use within the context of protein localisation, since they frequently require microscopy techniques that enable images of higher contrast (e.g. phase contrast microscopy or additional dyes) or can only be employed with too low magnifications. Therefore, this article introduces a novel approach to the robust automatic recognition of unstained living cells in bright-field microscope images. Here, the focus is on the automatic segmentation of cells.
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Titel des Konferenzbandes
Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA)
Seite
158-172
Konferenz
International Conference on Mass-Data Analysis of Images and Signals (MDA)
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Tscherepanow M, Zöllner F, Hillebrand M, Kummert F. Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images. In: Perner P, Salvetti O, eds. Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA). Berlin: Springer; 2008: 158-172.
Tscherepanow, M., Zöllner, F., Hillebrand, M., & Kummert, F. (2008). Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images. In P. Perner & O. Salvetti (Eds.), Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA) (pp. 158-172). Berlin: Springer. doi:10.1007/978-3-540-70715-8_13
Tscherepanow, M., Zöllner, F., Hillebrand, M., and Kummert, F. (2008). “Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images” in Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA), Perner, P., and Salvetti, O. eds. (Berlin: Springer), 158-172.
Tscherepanow, M., et al., 2008. Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images. In P. Perner & O. Salvetti, eds. Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA). Berlin: Springer, pp. 158-172.
M. Tscherepanow, et al., “Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images”, Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA), P. Perner and O. Salvetti, eds., Berlin: Springer, 2008, pp.158-172.
Tscherepanow, M., Zöllner, F., Hillebrand, M., Kummert, F.: Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images. In: Perner, P. and Salvetti, O. (eds.) Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA). p. 158-172. Springer, Berlin (2008).
Tscherepanow, Marko, Zöllner, Frank, Hillebrand, Matthias, and Kummert, Franz. “Automatic Segmentation of Unstained Living Cells in Bright-Field Microscope Images”. Proceedings of the International Conference on Mass-Data Analysis of Images and Signals (MDA). Ed. Petra Perner and Ovidio Salvetti. Berlin: Springer, 2008. 158-172.
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