Bayesian posterior density estimation reveals degeneracy in three-dimensional multiple emitter localization.

ABSTRACT: Single-molecule localization microscopy requires sparse activation of emitters to circumvent the diffraction limit. In densely labeled or thick samples, overlap of emitter images is inevitable. Single-molecule localization of these samples results in a biased parameter estimate with a wrong model of the number of emitters. On the other hand, multiple emitter fitting suffers from point spread function degeneracy, which increases model and parameter uncertainty. To better estimate the model, parameters and uncertainties, a three-dimensional Bayesian multiple emitter fitting algorithm was constructed using Reversible Jump Markov Chain Monte Carlo. It reconstructs the posterior density of both the model and the parameters, namely the three-dimensional position and photon intensity, of overlapp

SUBMITTER: van Dijk R 

PROVIDER: S-EPMC10724183 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature