K-factor image deshadowing for three-dimensional fluorescence microscopy

The ability to track single fluorescent particles within a three dimensional (3D) cellular environment can provide valuable insights into cellular processes. In this paper, we present a modified nonlinear image decomposition technique called K-factor that reshapes the 3D point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The method increases localization accuracy by similar to 60% with compare to regular Gaussian fitting, and improves minimal resolvable distance between overlapping PSFs by similar to 50%. The algorithm was tested both on simulated data and experimentally.