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.
Highlights
Since the invention of Stimulated Emission Depletion (STED) Microscopy by Stefan Hell at the beginning of the nineties of the last century [1, 2], the field of super-resolution fluorescence microscopy has seen an dramatic development with the invention and refinement of a plethora of new techniques such as Photoactivated Localization Microscopy (PALM) [3] or Stochastic Optical Reconstruction Microscopy (STORM) [4], for a recent review see e.g. [5]
When imaging a sample with a wide-field microscope, each emitter in the sample contributes to the final image on the detector with some intensity distribution U(r − r ) which is called the Point Spread Function (PSF) of the microscope, where r denotes the position on the camera and r the position of an emitter in the sample
We have presented an easy and straightforward way ho to solve the “pixelation” problem of Stochastic Optical Fluctuation Imaging (SOFI)
Summary
Since the invention of Stimulated Emission Depletion (STED) Microscopy by Stefan Hell at the beginning of the nineties of the last century [1, 2], the field of super-resolution fluorescence microscopy (microscopy beyond Abbe’s classical resolution limit) has seen an dramatic development with the invention and refinement of a plethora of new techniques such as Photoactivated Localization Microscopy (PALM) [3] or Stochastic Optical Reconstruction Microscopy (STORM) [4], for a recent review see e.g. [5]. Padding the Fourier-transformed image with zeros will does not change or alter its information content, but after back-transforming such a padded image into real space, one obtains an image with increased pixel number of reduced size This procedure represents a method of exact interpolation of the original image, without introduction of artifacts. Using this interpolation scheme, the pixel size of the original frames of a recorded movie can be adapted to the desired spatial resolution delivered by SOFI. We call this combination of SOFI with Fourier-transform based interpolation Fourier-SOFI or fSOFI, and in what follows, we give a detailed description of its principles and exemplify the method on imaging fluorescently labeled neurons
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