Bayesian Estimation of the Axial Position in Astigmatism-Based Three-Dimensional Particle Tracking

Abstract

Accurate estimation of the axial position of a molecule using a single lateral image remains a challenge in fluorescent single particle tracking. Here, a principled algorithm for the Bayesian estimation of the axial position of a molecule in three-dimensional astigmatism-based particle tracking is proposed. This technique uses the data from a calibration image set to derive the position without assuming a functional form for the abberated defocusing curve. Using a calibration image set from forty 57 nm beads, the axial position is calculated, and the error associated with position estimation is discussed. This method is compared to previously published algorithms.