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Proceedings Paper

Adaptive platform for fluorescence microscopy-based high-content screening
Author(s): Matthias Geisbauer; Thorsten Röder; Yang Chen; Alois Knoll; Rainer Uhl
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Paper Abstract

Fluorescence microscopy has become a widely used tool for the study of medically relevant intra- and intercellular processes. Extracting meaningful information out of a bulk of acquired images is usually performed during a separate post-processing task. Thus capturing raw data results in an unnecessary huge number of images, whereas usually only a few images really show the particular information that is searched for. Here we propose a novel automated high-content microscope system, which enables experiments to be carried out with only a minimum of human interaction. It facilitates a huge speed-increase for cell biology research and its applications compared to the widely performed workflows. Our fluorescence microscopy system can automatically execute application-dependent data processing algorithms during the actual experiment. They are used for image contrast enhancement, cell segmentation and/or cell property evaluation. On-the-fly retrieved information is used to reduce data and concomitantly control the experiment process in real-time. Resulting in a closed loop of perception and action the system can greatly decrease the amount of stored data on one hand and increases the relative valuable data content on the other hand. We demonstrate our approach by addressing the problem of automatically finding cells with a particular combination of labeled receptors and then selectively stimulate them with antagonists or agonists. The results are then compared against the results of traditional, static systems.

Paper Details

Date Published: 23 March 2010
PDF: 9 pages
Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76224D (23 March 2010); doi: 10.1117/12.844280
Show Author Affiliations
Matthias Geisbauer, BioImaging Zentrum der Ludwig-Maximilians-Univ. (Germany)
Thorsten Röder, Technische Univ. München (Germany)
Yang Chen, Technische Univ. München (Germany)
Alois Knoll, Technische Univ. München (Germany)
Rainer Uhl, BioImaging Zentrum der Ludwig-Maximilians-Univ. (Germany)


Published in SPIE Proceedings Vol. 7622:
Medical Imaging 2010: Physics of Medical Imaging
Ehsan Samei; Norbert J. Pelc, Editor(s)

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