Abstract
Non-invasive and marker-free monitoring of living cells can be accomplished by vector contrast scanning acoustic microscopy. In this paper, the signal processing required for creating time-lapse movies of mesenchymal stem cells is discussed. This includes electronic signal processing, autofocusing and image processing. Prior to each recorded image the focusing transducer is moved away from the sample until no echo signal is received. This allows direct measurement of the offset vector caused by internal lens echoes. The offset vector can then be subtracted from the following vector-contrast image. For subsequent autofocusing the transducer is moved closer to the sample until the maximum of the signal in reflection is passed. The transducer position for the maximum reflected signal is determined by respective software and adjusted accordingly. Autofocusing is a requirement for tiled scans where a piezo-scanner and an automatic microscope stage are combined to increase the field of view. As there are typically thousands of images involved in a single movie, batch image processing routines are required. Customized plugins for ImageJ were developed to combine specialized functions for vector contrast data processing with standard image processing capabilities. The motility of a population of ovine mesenchymal stem cells was continuously recorded for 8 h. The detection scheme including experimental details is presented and applications including time-lapse imaging are demonstrated and discussed.
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Acknowledgments
We would like to thank Matthias Zscharnak, Claudia Pösel and Frank Peinemann for providing the cells and the Federal Ministry of Education and Research (BMBF grant 0313836, MS CartPro) for financial support.
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von Buttlar, M., Mohamed, E., Grill, W. (2011). Signal Processing for Time-Lapse Cell Imaging with Vector-Contrast Scanning Acoustic Microscopy. In: André, M., Jones, J., Lee, H. (eds) Acoustical Imaging. Acoustical Imaging, vol 30. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3255-3_17
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DOI: https://doi.org/10.1007/978-90-481-3255-3_17
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