Measurement-based estimation of global pupil functions in 3D localization microscopy

TL;DR

This paper introduces a maximum likelihood phase retrieval method to accurately calibrate the pupil function in 3D localization microscopy, improving localization precision and accuracy over traditional models.

Contribution

It presents a novel phase retrieval approach for experimentally calibrating the pupil function, enhancing 3D localization microscopy performance.

Findings

Significant improvement in localization accuracy and precision.

Near theoretical limits of localization precision achieved.

Reproducibility of the calibration procedure confirmed.

Abstract

We report the use of a phase retrieval procedure based on maximum likelihood estimation (MLE) to produce an improved, experimentally calibrated model of a point spread function (PSF) for use in three-dimensional (3D) localization microscopy experiments. The method estimates a global pupil phase function (which includes both the PSF and system aberrations) over the full axial range from a simple calibration scan. The pupil function is used to refine the PSF model and hence enable superior localizations from experimental data. To demonstrate the utility of the procedure, we apply it to experimental data acquired with a microscope employing a tetrapod PSF with a 6 micron axial range. The phase-retrieved model demonstrates significant improvements in both accuracy and precision of 3D localizations relative to the model based on scalar diffraction theory. The localization precision of the phase-retrieved model is shown to be near the limits imposed by estimation theory, and the reproducibility of the procedure is characterized and discussed. Code which performs the phase retrieval algorithm is provided.