Fast reconstruction algorithm for structured illumination microscopy.

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.

[1]  K. O’Holleran,et al.  Optimized approaches for optical sectioning and resolution enhancement in 2D structured illumination microscopy , 2014, Biomedical optics express.

[2]  J. Siegel,et al.  Time‐domain whole‐field fluorescence lifetime imaging with optical sectioning , 2001, Journal of microscopy.

[3]  Hui Cao,et al.  Generating Non-Rayleigh Speckles with Tailored Intensity Statistics , 2014, 1401.7662.

[4]  Laura Waller,et al.  Structured illumination microscopy with unknown patterns and a statistical prior , 2016, Biomedical optics express.

[5]  Kai Wicker,et al.  Non-iterative determination of pattern phase in structured illumination microscopy using auto-correlations in Fourier space. , 2013, Optics express.

[6]  M. Gustafsson Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy , 2000, Journal of microscopy.

[7]  Clemens F. Kaminski,et al.  Frontiers in structured illumination microscopy , 2016 .

[8]  Anne Sentenac,et al.  Structured illumination microscopy using unknown speckle patterns , 2012, Nature Photonics.

[9]  Multi-color live-cell super-resolution volume imaging with multi-angle interference microscopy , 2018, Nature Communications.

[10]  M. Gustafsson Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Michael J Rust,et al.  Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) , 2006, Nature Methods.

[12]  A. Descloux,et al.  Parameter-free image resolution estimation based on decorrelation analysis , 2019, Nature Methods.

[13]  Michael D. Mason,et al.  Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. , 2006, Biophysical journal.

[14]  Xu Liu,et al.  Inverse matrix based phase estimation algorithm for structured illumination microscopy. , 2018, Biomedical optics express.

[15]  Reto Fiolka,et al.  Phase optimisation for structured illumination microscopy. , 2013, Optics express.

[16]  S. Hell,et al.  Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. , 1994, Optics letters.

[17]  Giuliano Scarcelli,et al.  Sub-Rayleigh imaging via speckle illumination. , 2013, Optics letters.

[18]  J. Lippincott-Schwartz,et al.  Imaging Intracellular Fluorescent Proteins at Nanometer Resolution , 2006, Science.

[19]  Bryant B. Chhun,et al.  Super-Resolution Video Microscopy of Live Cells by Structured Illumination , 2009, Nature Methods.

[20]  Jong Chul Ye,et al.  Fluorescent microscopy beyond diffraction limits using speckle illumination and joint support recovery , 2013, Scientific Reports.