Structured illumination microscopy (SIM) is a powerful technique for providing super-resolution imaging, but its reconstruction algorithm, i.e., linear reconstruction structured illumination microscopy (LRSIM) algorithm in the Fourier domain, limits the imaging speed due to its computational effort. Here, we present a novel reconstruction algorithm that can directly process SIM data in the spatial domain. Compared to LRSIM, this approach uses the same number of frames to achieve a comparable resolution but with a much faster processing speed. Our algorithm was verified on both simulated and experimental data using sinusoidal pattern illumination. Moreover, this algorithm is also applicable for speckle pattern illumination.

In super-resolution optical microscopes, aberrations often compromise the image performances by reducing its resolution and contrast. In previous works, the aberrations in stimulated emission depletion (STED) microscopy and single-molecule localization microscopy (SMLM) have been well-investigated, while the research on the aberrations in structured illumination microscopy (SIM) is not sufficient, the researchers always poured attention into aberrations only in the detection path. In this paper, we investigate the aberrations in SIM in a comprehensive manner, and their causes and effects on both the illumination and the detection paths are discussed. The aberrations in the illumination path may distort illumination patterns, and deteriorate the final images, together with the aberrations in the detection path. In addition, several non-aberration-related factors, especially the misalignment of the incident beams with respect to the objective pupil, can also dramatically influence the performances of SIM. The analysis provides the theoretical basis and for optimizing a SIM system.

Stimulated emission depletion (STED) fluorescence nanoscopy allows the three-dimensional (3D) visualization of nanoscale subcellular structures, providing unique insights into their spatial organization. However, 3D-STED imaging and quantification of dense features are obstructed by the low signal-to-background ratio (SBR) resulting from optical aberrations and out-of-focus background. Here, combining adaptive optics elements, we present an easy-to-implement, flexible, and effective method to improve the SBR by dynamic phase switching. By switching to a counterclockwise vortex phase mask and a top-hat one with an incorrect inner radius, the depletion pattern features a nonzero-intensity center, enabling accurate background recordings. When the recorded background is subtracted from the aberration-corrected 3D-STED image, the SBR in dense sample areas can be improved by a factor of 3−7 times. We demonstrate our method on various dense subcellular structures, showing more advantages than the software-based background subtraction algorithms.