Simultaneous tracking of multiple particles and sensor position estimation in fluorescence microscopy images

Abstract

Photoactivated Localization Microscopy (PALM) is a technique which allows the localization of particles smaller than the resolution of the microscope and can be used to analyze intracellular particle motion. Images acquired with this technique, however, are noisy, which complicates particle detection, and tracking the particles is complicated due to the presence of multiple objects at any given time. Additionally, the microscope head may drift by small amounts, which reduces the precision of the localization method. This paper proposes solutions to these problems based on the PHD Filter. To begin, a method for extracting protein positions from microscopy images is proposed. Tracking is provided on the extracted data using the PHD Filter framework for multiple object tracking, and a specially adapted particle filter for bias estimation is developed which exploits the PHD filter to estimate the likeliest position of the microscope. Results are shown using simulated data, and data acquired from a fluorescence microscopy experiment.