AI Article Synopsis

  • SOFI is a super-resolution microscopy technique that enhances image resolution by analyzing the blinking of fluorescent emitters rather than tracking individual molecules like PALM or STORM.
  • A key issue with traditional SOFI is that the resolution of the final image matches the pixel size of the original images, which can be problematic when aiming for finer details.
  • The authors propose a new, simpler method using Fourier transform-based interpolation to effectively address this resolution challenge, demonstrating its effectiveness with both simulated and real data.

Article Abstract

Stochastic Optical Fluctuation Imaging (SOFI) is a super-resolution fluorescence microscopy technique which allows to enhance the spatial resolution of an image by evaluating the temporal fluctuations of blinking fluorescent emitters. SOFI is not based on the identification and localization of single molecules such as in the widely used Photoactivation Localization Microsopy (PALM) or Stochastic Optical Reconstruction Microscopy (STORM), but computes a superresolved image via temporal cumulants from a recorded movie. A technical challenge hereby is that, when directly applying the SOFI algorithm to a movie of raw images, the pixel size of the final SOFI image is the same as that of the original images, which becomes problematic when the final SOFI resolution is much smaller than this value. In the past, sophisticated cross-correlation schemes have been used for tackling this problem. Here, we present an alternative, exact, straightforward, and simple solution using an interpolation scheme based on Fourier transforms. We exemplify the method on simulated and experimental data.

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Source
http://dx.doi.org/10.1364/OE.23.016154DOI Listing

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