An Adaptive Algorithm for Multimodal Focus Functions in Automated Fluorescence Microscopy

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Authors

BRÁZDILOVÁ Silvie Luisa KOZUBEK Michal

Year of publication 2008
Type Article in Proceedings
Conference Medical Imaging Conference
MU Faculty or unit

Faculty of Informatics

Citation
Field Use of computers, robotics and its application
Keywords automated microscopy; focus function
Description This work presents a new autofocusing algorithm for fluorescence microscopy that aims at finding all significant planes of focus in cases that the focus function applied on real data is not unimodal, which is often the case. First, nineteen focus functions are tested and their ability to show local maxima clearly is evaluated. The results show that only six focus functions work successfully. Then adaptively variable step size is introduced because wide range of possible focus positions has to be passed not to miss a local maximum. The algorithm therefore assesses the steepness of the focus function on-line so that it can decide whether bigger or smaller step size should be used for acquiring next image. It is shown that for Normalized Variance, the knowledge about steepness can be obtained after normalizing with respect to the theoretical maximum of this function. The resulting algorithm is reliable and efficient compared to a simple procedure with constant steps.
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