CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs
Burgemeister S, Nattkemper TW, Noll T, Hoffrogge R, Flaschel E (2010)
JOURNAL OF BIOTECHNOLOGY 149(4): 310-316.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Einrichtung
Centrum für Biotechnologie > Arbeitsgruppe T. Nattkemper
Centrum für Biotechnologie > Institut für Biochemie und Biotechnik
Technische Fakultät > AG Biodata Mining
Technische Fakultät > AG Fermentationstechnik
Centrum für Biotechnologie > Institut für Bioinformatik
Center of Excellence - Cognitive Interaction Technology CITEC
Centrum für Biotechnologie > Arbeitsgruppe T. Noll
Centrum für Biotechnologie > Arbeitsgruppe E. Flaschel
Technische Fakultät > AG Zellkulturtechnik
Centrum für Biotechnologie > Institut für Biochemie und Biotechnik
Technische Fakultät > AG Biodata Mining
Technische Fakultät > AG Fermentationstechnik
Centrum für Biotechnologie > Institut für Bioinformatik
Center of Excellence - Cognitive Interaction Technology CITEC
Centrum für Biotechnologie > Arbeitsgruppe T. Noll
Centrum für Biotechnologie > Arbeitsgruppe E. Flaschel
Technische Fakultät > AG Zellkulturtechnik
Abstract / Bemerkung
Online monitoring of cell density and cell viability is a challenging but essential task to control and optimize biotechnical processes and is of particular interest for the growing field of animal cell cultures. For this purpose, we introduce an optical approach for automated cell detection and viability classification of suspended mammalian cells. Our proposed system CellViCAM is capable of evaluating dark field micrographs by means of several image processing and supervised machine learning techniques without the use of any dyes or fluorescent labeling. Using a human cell line as the reference culture, an efficient cell detection procedure has been established also enabling a cell density estimation. Furthermore, a comprehensive but reagent-free viability analysis, based on a semi-automatic training data generation, has been developed. By means of an extensive validation dataset we can show that the CellViCAM approach can be considered as an equivalent to staining-based methods and moreover, how it provides a technical platform for a more differentiated cell state classification into living, necrotic, early and late apoptosis. (C) 2010 Elsevier B.V. All rights reserved.
Stichworte
microscopy;
Machine learning;
Image processing;
Apoptosis;
Cell viability analysis;
Dark field;
Animal cell cultures
Erscheinungsjahr
2010
Zeitschriftentitel
JOURNAL OF BIOTECHNOLOGY
Band
149
Ausgabe
4
Seite(n)
310-316
ISSN
0168-1656
Page URI
https://pub.uni-bielefeld.de/record/1929340
Zitieren
Burgemeister S, Nattkemper TW, Noll T, Hoffrogge R, Flaschel E. CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs. JOURNAL OF BIOTECHNOLOGY. 2010;149(4):310-316.
Burgemeister, S., Nattkemper, T. W., Noll, T., Hoffrogge, R., & Flaschel, E. (2010). CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs. JOURNAL OF BIOTECHNOLOGY, 149(4), 310-316. https://doi.org/10.1016/j.jbiotec.2010.07.020
Burgemeister, Sebastian, Nattkemper, Tim Wilhelm, Noll, Thomas, Hoffrogge, Raimund, and Flaschel, Erwin. 2010. “CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs”. JOURNAL OF BIOTECHNOLOGY 149 (4): 310-316.
Burgemeister, S., Nattkemper, T. W., Noll, T., Hoffrogge, R., and Flaschel, E. (2010). CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs. JOURNAL OF BIOTECHNOLOGY 149, 310-316.
Burgemeister, S., et al., 2010. CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs. JOURNAL OF BIOTECHNOLOGY, 149(4), p 310-316.
S. Burgemeister, et al., “CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs”, JOURNAL OF BIOTECHNOLOGY, vol. 149, 2010, pp. 310-316.
Burgemeister, S., Nattkemper, T.W., Noll, T., Hoffrogge, R., Flaschel, E.: CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs. JOURNAL OF BIOTECHNOLOGY. 149, 310-316 (2010).
Burgemeister, Sebastian, Nattkemper, Tim Wilhelm, Noll, Thomas, Hoffrogge, Raimund, and Flaschel, Erwin. “CellViCAM-Cell viability classification for animal cell cultures using dark field micrographs”. JOURNAL OF BIOTECHNOLOGY 149.4 (2010): 310-316.
Daten bereitgestellt von European Bioinformatics Institute (EBI)
3 Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
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