Investigation of the numerics of point spread function integration in single molecule localization.

The computation of point spread functions, which are typically used to model the image profile of a single molecule, represents a central task in the analysis of single molecule microscopy data. To determine how the accuracy of the computation affects how well a single molecule can be localized, we investigate how the fineness with which the point spread function is integrated over an image pixel impacts the performance of the maximum likelihood location estimator. We consider both the Airy and the two-dimensional Gaussian point spread functions. Our results show that the point spread function needs to be adequately integrated over a pixel to ensure that the estimator closely recovers the true location of the single molecule with an accuracy that is comparable to the best possible accuracy as determined using the Fisher information formalism. Importantly, if integration with an insufficiently fine step size is carried out, the resulting estimates can be significantly different from the true location, particularly when the image data is acquired at relatively low magnifications. We also present a methodology for determining an adequate step size for integrating the point spread function.

[1]  R. Sheppard,et al.  A matrix method for calculating the three-dimensional irradiance distribution in the focal region of a convergent beam , 2003 .

[2]  Michael J Rust,et al.  Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) , 2006, Nature Methods.

[3]  Jerry Chao,et al.  Fisher information matrix for branching processes with application to electron-multiplying charge-coupled devices , 2012, Multidimens. Syst. Signal Process..

[4]  Michael D. Mason,et al.  Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. , 2006, Biophysical journal.

[5]  Keith A. Lidke,et al.  Fast, single-molecule localization that achieves theoretically minimum uncertainty , 2010, Nature Methods.

[6]  José-Angel Conchello,et al.  Numerical evaluation of Hankel transforms for oscillating functions. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[7]  M K Cheezum,et al.  Quantitative comparison of algorithms for tracking single fluorescent particles. , 2001, Biophysical journal.

[8]  T. Kues,et al.  Imaging and tracking of single GFP molecules in solution. , 2000, Biophysical journal.

[9]  S. Ram,et al.  Localization accuracy in single-molecule microscopy. , 2004, Biophysical journal.

[10]  J. Lippincott-Schwartz,et al.  Imaging Intracellular Fluorescent Proteins at Nanometer Resolution , 2006, Science.

[11]  W E Moerner,et al.  New directions in single-molecule imaging and analysis , 2007, Proceedings of the National Academy of Sciences.

[12]  Jerry Chao,et al.  Quantitative study of single molecule location estimation techniques. , 2009, Optics express.

[13]  A. Sergé,et al.  Dynamic multiple-target tracing to probe spatiotemporal cartography of cell membranes , 2008, Nature Methods.

[14]  W. Webb,et al.  Precise nanometer localization analysis for individual fluorescent probes. , 2002, Biophysical journal.

[15]  Sripad Ram,et al.  A novel resolution measure for optical microscopes: stochastic analysis of the performance limits , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[16]  Sripad Ram,et al.  A Stochastic Analysis of Performance Limits for Optical Microscopes , 2006, Multidimens. Syst. Signal Process..