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Selection and Tuning of a Fast and Simple Phase-Contrast Microscopy Image Segmentation Algorithm for Measuring Myoblast Growth Kinetics in an Automated Manner

Published online by Cambridge University Press:  30 May 2013

Pierre-Marc Juneau ,
Alain Garnier  and
Carl Duchesne
Pierre-Marc Juneau
Affiliation:
Department of Chemical Engineering, Université Laval, Pavillon Adrien-Pouliot, 1065 ave. de la Médecine, Québec City, Québec G1V 0A6, Canada
Alain Garnier
Affiliation:
Department of Chemical Engineering, Université Laval, Pavillon Adrien-Pouliot, 1065 ave. de la Médecine, Québec City, Québec G1V 0A6, Canada
Carl Duchesne*
Affiliation:
Department of Chemical Engineering, Université Laval, Pavillon Adrien-Pouliot, 1065 ave. de la Médecine, Québec City, Québec G1V 0A6, Canada
*
*Corresponding author. E-mail: [email protected]
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Abstract

Acquiring and processing phase-contrast microscopy images in wide-field long-term live-cell imaging and high-throughput screening applications is still a challenge as the methodology and algorithms used must be fast, simple to use and tune, and as minimally intrusive as possible. In this paper, we developed a simple and fast algorithm to compute the cell-covered surface (degree of confluence) in phase-contrast microscopy images. This segmentation algorithm is based on a range filter of a specified size, a minimum range threshold, and a minimum object size threshold. These parameters were adjusted in order to maximize the F-measure function on a calibration set of 200 hand-segmented images, and its performance was compared with other algorithms proposed in the literature. A set of one million images from 37 myoblast cell cultures under different conditions were processed to obtain their cell-covered surface against time. The data were used to fit exponential and logistic models, and the analysis showed a linear relationship between the kinetic parameters and passage number and highlighted the effect of culture medium quality on cell growth kinetics. This algorithm could be used for real-time monitoring of cell cultures and for high-throughput screening experiments upon adequate tuning.

Keywords

phase-contrast microscopylive-cell imagingsegmentationcell-covered surfacedegree of confluencemyoblastsgrowth kineticspassage numberalgorithm tuningalgorithm selection
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 19 , Issue 4 , August 2013 , pp. 855 - 866
Copyright
Copyright © Microscopy Society of America 2013 

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