Enhanced temporal and spatial resolution in super‐resolution covariance imaging algorithm with deconvolution optimization

Abstract

Based on the numerical analysis that covariance exhibits superior statistical precision than cumulant and variance, a new SOFI algorithm by calculating the n orders covariance for each pixel is presented with an almost 2n‐fold resolution improvement, which can be enhanced to 2n via deconvolution. An optimized deconvolution is also proposed by calculating the (n + 1) order SD associated with each n order covariance pixel, and introducing the results into the deconvolution as a damping factor to suppress noise generation. Moreover, a re‐deconvolution of the covariance image with the covariance‐equivalent point spread function is used to further increase the final resolution by above 2‐fold. Simulated and experimental results show that this algorithm can significantly increase the temporal–spatial resolution of SOFI, meanwhile, preserve the sample's structure. Thus, a resolution of 58 nm is achieved for 20 experimental images, and the corresponding acquisition time is 0.8 seconds.

Enhancing detectable fluorescence fluctuation for high-throughput and four-dimensional live-cell super-resolution imaging

“…In comparison, SACD is insensitive to the SNR and contrast conditions and can effectively reconstruct high-fidelity SR images with minimum input. Next, to further demonstrate its superiority, we created more complex structures, i.e., rings with different diameters, and compared SACD against other advanced SOFI reconstruction methods 31-33 ( Methods, Extended Data Fig. 5, Supplementary Note 2 ).…”

“…The effective on/off contrast ratio is influenced by the unessential fluorescence, and the effective signal-to-noise ratio (SNR) condition dominated by inevitable readout noise, dark current noise, and shot noise of the sensor ( Extended Data Fig. 1a ), will affect the accuracy of cumulant calculation and the quality of the reconstrued image 19, 26, 33, 42, 43 . Thus, the real fluorescent content can be given by: where the represents the mixed influence of the cytosol background and baseline noise signal at position r k .…”

Enhanced detection of fluorescence fluctuations for high-throughput super-resolution imaging

“…The effective on/off contrast ratio is influenced by the unessential fluorescence, and the effective signal-to-noise ratio (SNR) condition dominated by inevitable readout noise, dark current noise, and shot noise of the sensor (Extended Data Fig. 1a), will affect the accuracy of cumulant calculation and the quality of the reconstrued image 19,26,33,42,43 . Thus, the real fluorescent content can be given by:…”

“…Next, to further demonstrate its superiority, we created more complex structures, i.e., rings with different diameters, and compared SACD against other advanced SOFI reconstruction methods [31][32][33] (Methods, Extended Data Fig. 5, Supplementary Note 2).…”

“…Reconstruction algorithms and their parameters for fluorescence fluctuation-based data. We compare performances against three other modified SOFI methods: SOFI-wavelet 32 , SOFI-RL 31,45 , and RD-Covar 33 (covariance calculation followed by RL deconvolution); and 5 other freely available software packages: SRRF 13 , ESI 15 , HAWK 50 , ThunderSTORM 51 , and bSOFI 45 . Notably, because the three modified SOFI methods are not open-sourced, we implemented them with adherence to the published work.…”