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    Motion artefact detection in structured illumination microscopy for live cell imaging
    (Washington, DC : Optical Society of America, 2016) Förster, Ronny; Wicker, Kai; Müller, Walter; Jost, Aurélie; Heintzmann, Rainer
    The reconstruction process of structured illumination microscopy (SIM) creates substantial artefacts if the specimen has moved during the acquisition. This reduces the applicability of SIM for live cell imaging, because these artefacts cannot always be recognized as such in the final image. A movement is not necessarily visible in the raw data, due to the varying excitation patterns and the photon noise. We present a method to detect motion by extracting and comparing two independent 3D wide-field images out of the standard SIM raw data without needing additional images. Their difference reveals moving objects overlaid with noise, which are distinguished by a probability theory-based analysis. Our algorithm tags motion-artefacts in the final high-resolution image for the first time, preventing the end-user from misinterpreting the data. We show and explain different types of artefacts and demonstrate our algorithm on a living cell.
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    Automated distinction of shearing and distortion artefacts in structured illumination microscopy
    (Washington D.C. : Optical Society of America, 2018) Förster, Ronny; Müller, Walter; Richter, Renè; Heintzmann, Rainer
    Any motion during an image acquisition leads to an artefact in the final image. Structured illumination microscopy (SIM) combines several raw images into one high-resolution image and is thus particularly prone to these motion artefacts. Their unpredictable shape cannot easily be distinguished from real high-resolution content. We previously implemented a motion detection specifically for SIM, which had two shortcomings which are solved here. First, the brightness dependency of the motion signal is removed. Second, the empirical threshold of the calculated motion signal was not a threshold at a maximum allowed artefact. Here we investigate which artefacts are still acceptable and which linear movement creates them. Thus, the motion signal is linked with the maximal strength of the expected artefact. A signal-to-noise analysis including classification successfully distinguishes between artefact-free imaging, shearing and distortion artefacts in biological specimens. A shearing, as in wide-field microscopy, is the dominant reconstruction artefact, while distortions arise not until surprisingly fast movements.