Image quality in single-molecule localization microscopy depends largely on the accuracy and precision of the localizations. While under ideal imaging conditions, the theoretically obtainable precision and accuracy are achieved; in practice, this changes if (field-dependent) aberrations are present. Currently, there is no simple way to measure and incorporate these aberrations into the point-spread function (PSF) fitting; therefore, the aberrations are often taken as constant or neglected altogether. Here we introduce a model-based approach to estimate the field-dependent aberration directly from single-molecule data without a calibration step. This is made possible by using nodal aberration theory to incorporate the field dependency of aberrations into our fully vectorial PSF model. This results in a limited set of aberration fit parameters that can be extracted from the raw frames without a bead calibration measurement, also in retrospect. The software implementation is computationally efficient, enabling the fitting of a full 2D or 3D dataset within a few minutes. We demonstrate our method on 2D and 3D localization data of microtubuli, nuclear pore complexes, and nuclear lamina over fields of view of up to 180 µm and compare it with Gaussian fitting, spline-based fitting, and a deep-learning-based approach.

We address resolution assessment for (light super-resolution) microscopy imaging. In modalities where imaging is not diffraction limited, correlation between two noise independent images is the standard way to infer the resolution. Here we take away the need for two noise independent images by computationally splitting one image acquisition into two noise independent realizations. This procedure generates two Poisson noise distributed images if the input is Poissonian distributed. As most modern cameras are shot-noise limited this procedure is directly applicable. However, also in the presence of readout noise we can compute the resolution faithfully via a correction factor. We evaluate our method on simulations and experimental data of widefield microscopy, STED microscopy, rescan confocal microscopy, image scanning microscopy, conventional confocal microscopy, and transmission electron microscopy. In all situations we find that using one image instead of two results in the same computed image resolution.