METHOD OF IMAGE EVALUATION FOR SIM MICROSCOPY AND SIM MICROSCOPY METHOD

A method of image evaluation when performing SIM microscopy on a sample includes: A) providing n raw images of the sample, which were each generated by illuminating the sample with an individually positioned SIM illumination pattern and imaging the sample in accordance with a point spread function,...

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Bibliographische Detailangaben
Hauptverfasser: Schaefer, Lutz, KLEPPE, Ingo, Novikau, Yauheni
Format: Patent
Sprache:eng
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Zusammenfassung:A method of image evaluation when performing SIM microscopy on a sample includes: A) providing n raw images of the sample, which were each generated by illuminating the sample with an individually positioned SIM illumination pattern and imaging the sample in accordance with a point spread function, B) providing (S1) n illumination pattern functions, which each describe one of the individually positioned SIM illumination patterns, C) providing (S1) the point spread function and D) Carrying out an iteration method, which includes following iteration steps a) to e), as follows: a) providing an estimated image of the sample, b) generating simulated raw images, in each case by image processing of the estimated image using the point spread function and one of the n illumination pattern functions such that n simulated raw images are obtained, c) assigning each of the n simulated raw images to that of the n provided raw images which was generated by the illumination pattern that corresponds to the illumination pattern function used to generate the simulated raw image, and calculating n correction raw images by the comparison of each provided raw image with the simulated raw image assigned thereto, d) generating a correction image by combining image processing of the n correction raw images using the point spread function and the n illumination pattern functions, wherein a filtering step is carried out in each implementation of iteration step d), said filtering step suppressing a spatial fundamental frequency of the illumination pattern, and e) reconstructing the estimated image of the sample by means of the correction image and using the corrected estimated image of the sample as the estimated image of the sample in iteration step a) in the next run through the iteration.