Fig. 2: Evaluation and benchmarking of the robustness and generalization of SeReNet.
a, Raw measurements and SeReNet reconstruction results of a mitochondria-labeled L929 cell with different levels of mixed Poisson–Gaussian noises applied in simulation. NLL-MPG loss and L1 loss are compared. b, Multiscale structural similarity (MS-SSIM) curves over photon numbers, comparing different loss functions. c, Boxplot showing MS-SSIM indices obtained by different methods under low-photon (5–15) conditions. n = 11 experiments. P = 7.78 × 10−4. d, Measurement with artificially induced non-rigid motion and its counterparts, corrected by time-weighted algorithm and TW-Net. The coefficient map estimated by TW-Net is shown. e, Peak SNR (PSNR) curve versus different methods and coefficients. n = 9 views are shown as scatter points. f, SeReNet results without (w/o) and with (w/) preDAO after the input was contaminated by an induced aberration wavefront, the root mean square (r.m.s.) of which was set to one wavelength. The estimated wavefront by preDAO and ground truth are attached. GT, ground truth; λ, wavelength. g, Visualization of the amplitudes of 18 Zernike modes decomposed from the estimated pupils by preDAO (red) and the ground truth (blue). h, MS-SSIM curves versus aberration levels with and without preDAO. i, Boxplot showing MS-SSIM indices obtained by different methods with severe aberrations. The r.m.s. was set to one wavelength. n = 10 aberration patterns were used. P = 1.42 × 10−6, 1.50 × 10−6 from left to right. j, Test of generalization from the bubtub dataset to multiple kinds of experimentally captured structures. k, Boxplot showing MS-SSIM indices obtained by different methods, compared with the ground truth. n = 14 represents the number of samples. P = 1.01 × 10−4, 3.06 × 10−10, 5.10 × 10−3 from left to right. In boxplots: center line, median; box limits, lower and upper quartiles; whiskers, 1.5 × interquartile range. Asterisks represent significance levels tested with two-sided paired t-test, significance at P < 0.05. **P < 1 × 10−2; ***P < 1 × 10−3; ****P < 1 × 10−4. All networks were trained on synthetic bubtub dataset. Scale bars, 10 μm (a,d,f,j).
