This article presents a method that allows for reliable automated image acquisition of specimens with high information content in light microscopy with emphasis on fluorescence microscopy applications. Automated microscopy typically relies on autofocusing used for the analysis of information content behaviour along the z-axis within each field of view. However, in the case of a field of view containing more objects that do not lie precisely in one z-plane, traditional autofocusing methods fail due to their principle of operation. We avoid this issue by reducing the original problem to a set of simple and performable tasks: we divide the field of view into a small number of tiles and process each of them individually. The obtained results enable discovering z-planes with rich information content that remain hidden during global analysis of the whole field of view. Our approach therefore outperforms other acquisition methods including the manual one. A large part of the contribution is oriented towards practical application.

Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic

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