Structured illumination microscopy with noise-controlled image reconstructions
This week a study appeared in Nature Methods on the impact of noise on Structured Illumination Microscopy image reconstructions, and how this knowledge helps to make these reconstructions less sensitive to artefacts as well as to eliminate arbitrary user set parameters. The work was done by Carlas Smith, Kees Hagen, Jacob Hoogenboom, and Sjoerd Stallinga together with PhD-students and collaborators in Erasmus Medical Center and Oxford.
Super-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artifacts that limit their applicability for lower signal-to-noise data. Here we present a physically realistic noise model that explains the structured noise artifact, which we then use to motivate new complementary reconstruction approaches. True-Wiener-filtered SIM optimizes contrast given the available signal-to-noise ratio, and flat-noise SIM fully overcomes the structured noise artifact while maintaining resolving power. Both methods eliminate ad hoc user-adjustable reconstruction parameters in favor of physical parameters, enhancing objectivity. The new reconstructions point to a trade-off between contrast and a natural noise appearance. This trade-off can be partly overcome by further notch filtering but at the expense of a decrease in signal-to-noise ratio. The benefits of the proposed approaches are demonstrated on focal adhesion and tubulin samples in two and three dimensions, and on nanofabricated fluorescent test patterns.
