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Compendium Paper information and status C. Jackson, R. F. Murphy and
J. Kovačević, “Intelligent acquisition and learning of
fluorescence microscope data models,” IEEE Trans. Image Processing.
2009. To appear. Abstract We
propose a mathematical framework and algorithms both to build accurate models
of fluorescence microscope time series, as well as design intelligent
acquisition systems based on these models. Model building allows the
information contained in the 2D and 3D time series to be presented in a more
useful and concise form than the raw image data. This is particularly
relevant as the trend in biology tends more and more towards high-throughput
applications, and the resulting increase in the amount of acquired image data
makes visual inspection impractical. The intelligent acquisition system uses
an active learning approach to choose the acquisition regions that let us
build our model most efficiently, resulting in a more accurate model in a
shorter period of time, as well as in the reduction of the amount of photobleaching and phototoxicity
incurred during acquisition. We
demonstrate our our methodology by modeling the
dynamics of objects within a cell using particle filters. For intelligent
acquisition, we propose a set of algorithms to evaluate the information
contained in a given acquisition region, as well as the costs associated with
acquiring this region in terms of the resulting photobleaching
and phototoxicity and the amount of time taken for
acquisition. We use these algorithms to determine the optimal acquisition
strategy: where and when to acquire, as well as when to stop acquiring. Results
demonstrate accurate model building and large efficiency gains during
acquisition. Data All experiments in this paper
are based on synthetic tracks. These tracks are generated in the code
relating to the given experiment. Code The zipped archive contains
the readme file as well as the code to generate the results in the paper. This work is licensed under a
Creative Commons GNU General Public License. To view a copy of this license,
visit http://creativecommons.org/licenses/GPL/2.0.
If you use this code or any part thereof in your research or publication,
please also include a reference to this paper. Thank you! [download] Proofs NA Other material NA List of tested configurations 1. MATLAB 2007a on Windows XP Professional, SP2 For more information or to
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