Methods to Eliminate Localization Bias and Reduce Localization Error in Localization Microscopy Datasets with Non-Uniform Background Fluorescence

Abstract

Single molecule localization microscopy has become a standard tool for nanoscale imaging of biological systems. However, improper treatment of non-uniform background fluorescence can degrade image accuracy and precision. In particular this can be problematic in cases where the structure being imaged is correlated in space with high background fluorescence. Various methods have already been implemented for correction of background fluorescence. Here, we demonstrate that these background estimation and correction procedures lead to both systematic and random error in emitter localization, under experimentally relevant background conditions.