Fig. 2: eSRRF provides an automated reconstruction parameter search. | Nature Methods

Fig. 2: eSRRF provides an automated reconstruction parameter search.

From: High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation

Fig. 2

ac, Finding the optimal parameters to calculate the RGC. RSP and FRC resolution maps as functions of R and S reconstruction parameters for a live-cell TIRF imaging dataset published by Moeyaert et al.53 (a). COS-7 cells are expressing the membrane targeting domain of Lyn kinase–SkylanS and were imaged at 33 Hz. Combined QnR metric map showing the compromise between fidelity and FRC resolution (b). WF image, optimal eSRRF reconstruction (i), R = 1.5, S = 4), low-resolution reconstruction (ii), R = 0.5, S = 1) and low-fidelity reconstruction (iii), R = 3.5, S = 5) (c). d,e, Estimating the optimal time window for the eSRRF temporal analysis based on tSSIM. The SSIM metric is observed over time, after ~200 frames it displays a sharp drop (d). The optimal time window is marked by the blue line. A color overlay of two consecutive reconstructed eSRRF frames with the optimal parameters and a frame window of 200 frames displays notable differences between the structures (marked by i and ii), which would lead to motion blurring in case of a longer frame window (e). Scale bars, 20 µm (c,e) and 5 µm (ei(ii)).

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