  Single molecule localization microscopy (SMLM) techniques enable imaging
biological samples well beyond the diffraction limit of light, but they vary
significantly in their spatial and temporal resolutions. High-order statistical
analysis of temporal fluctuations as in superresolution optical fluctuation
imaging (SOFI) also enable imaging beyond diffraction limit, but usually at a
lower resolution as compared to SMLM. Since the same data format is acquired
for both methods, their algorithms can be applied to the same data set, and
thus may be combined synergistically to improve overall imaging performance.
Here, we find that SOFI converges much faster than SMLM, provides additive
information to SMLM, and can efficiently reject background. We then show how
SOFI-assisted SMLM imaging can improve SMLM image reconstruction by rejecting
common sources of background, especially under low signal-to-background
conditions. The performance of our approach was evaluated using a realistic
simulation of fluorescence imaging we developed and further demonstrated on
experimental SMLM images of the plasma membrane of activated fixed and live T
cells. Our approach significantly enhances SMLM performance under demanding
imaging conditions and could set an example for synergizing additional imaging
techniques.
