Extended Data Fig. 6: Quantitative comparison of CARE and PSSR-SF with PSSR-MF and Rolling Average (RA) methods for timelapse data.
From: Deep learning-based point-scanning super-resolution imaging
PSNR (a) and SSIM (b) quantification show a decrease in accuracy when applying RA to LR-CARE and LR-PSSR-SF, while multi-frame PSSR provides superior performance compared to LR-PSSR-SF and CARE before and after RA processing. Data points were color-coded based on different cells. See Fig. 4c for visualized comparisons, and Supplementary Video 6 for a video comparison of the entire timelapse for CARE, LR-PSSR-SF, LR-PSSR-SF-RA, and LR-PSSR-MF. N = 5 independent timelapses with n = 30 timepoints each, achieving similar results. All values are shown as mean ± SEM. ****p < 0.0001; Two-sided paired t-test.
