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Live-cell assays are used to study the dynamic functional cellular processes in high-content screening of drug discovery processes. The large amount of image data created during the screening requires automatic image-analysis procedures that can describe these dynamic processes. One class of tasks in this application is the tracking of cells and the description of the events and the changes in the cell characteristics so that the desired information can be extracted from it based on data-mining and knowledge-discovery methods. In this paper, we propose a similarity-based approach for motion detection of the entire cell. Results are given on a test series from a real drug discovery process.
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