Obtaining super-resolved images at the mesoscale through super-resolution radial fluctuations.

Abstract

Significance: Current super-resolution imaging techniques allow for a greater understanding of cellular structures; however, they are often complex or only have the ability to image a few cells at once. This small field of view (FOV) may not represent the behavior across the entire sample, and manual selection of regions of interest (ROIs) may introduce bias. It is possible to stitch and tile many small ROIs; however, this can result in artifacts across an image.

Aim: The aim is to achieve accurate super-resolved images across a large FOV ( $4.4\times 3.0\mathrm{mm}$ ).

Approach: We have applied super-resolution radial fluctuations processing in conjunction with the Mesolens, which has the unusual combination of a low-magnification and high numerical aperture, to obtain super-resolved images.

Results: We demonstrate it is possible to achieve images with a resolution of $446.3\pm 10.9\mathrm{nm}$ , providing a $\sim 1.6$ -fold improvement in spatial resolution, over an FOV of $4.4\times 3.0\mathrm{mm}$ , with minimal error, and consistent structural agreement.

Conclusions: We provide a simple method for obtaining accurate super-resolution images over a large FOV, allowing for a simultaneous understanding of both subcellular structures and their large-scale interactions.