Automated distinction of shearing and distortion artefacts in structured illumination microscopy

Abstract

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.