Research Article Published in Plos One

Expectation Maximization based Framework for Joint Localization and Parameter Estimation in Single Particle Tracking from Segmented Images [Journal Paper]

[Main contributions] – There are two primary contributions of this work. The first is the extension of our existing algorithms to data captured using an sCMOS camera. Due to their relatively low cost, high speed, and performance, sCMOS cameras are becoming popular tools for SPT data acquisition and including them in our EM-based approach extends the impact our algorithms can have. The second is the detailed, quantitative comparison of our EM based methods to a standard in the field, namely GF-MSD, and to an existing alternative that is also based on optimal estimation theory and which has previously been shown to outperform the standard approach in the analysis of diffusion, namely GF-MLE. This comparison is done across a wide range of SBRs and across a wide range of diffusion coefficients, validating the performance of our methods and guiding users in algorithm selection based on their particular experimental conditions [More …]. 

The following video (DOI: 10.5061/dryad.9w0vt4bf5) shows the relationship among trajectory driven by Brownian motion, observation, and properties of readout noise brought by sCMOS.