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Proceedings Paper

Comparison of estimation algorithms in single-molecule localization
Author(s): Anish V. Abraham; Sripad Ram; Jerry Chao; E. Sally Ward; Raimund J. Ober
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Paper Abstract

Different techniques have been advocated for estimating single molecule locations from microscopy images. The question arises as to which technique produces the most accurate results. Various factors, e.g. the stochastic nature of the photon emission/detection process, extraneous additive noise, pixelation, etc., result in the estimated single molecule location deviating from its true location. Here, we review the results presented by [Abraham et. al, Optics Express, 2009, 23352-23373], where the performance of the maximum likelihood and nonlinear least squares estimators for estimating single molecule locations are compared. Our results show that on average both estimators recover the true single molecule location in all scenarios. Comparing the standard deviations of the estimates, we find that in the absence of noise and modeling inaccuracies, the maximum likelihood estimator is more accurate than the non-linear least squares estimator, and attains the best achievable accuracy for the sets of experimental and imaging conditions tested. In the presence of noise and modeling inaccuracies, the maximum likelihood estimator produces results with consistent accuracy across various model mismatches and misspecifications. At high noise levels, neither estimator has an accuracy advantage over the other. We also present new results regarding the performance of the maximum likelihood estimator with respect to the objective function used to fit data containing both additive Gaussian and Poisson noise. Comparisons were also carried out between two localization accuracy measures derived previously. User-friendly software packages were developed for single molecule location estimation (EstimationTool) and localization accuracy calculations (FandPLimitTool).

Paper Details

Date Published: 24 February 2010
PDF: 7 pages
Proc. SPIE 7570, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVII, 757004 (24 February 2010); doi: 10.1117/12.842178
Show Author Affiliations
Anish V. Abraham, The Univ. of Texas at Dallas, (United States)
The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Sripad Ram, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Jerry Chao, The Univ. of Texas at Dallas (United States)
The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
E. Sally Ward, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Raimund J. Ober, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
The Univ. of Texas at Dallas (United States)


Published in SPIE Proceedings Vol. 7570:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVII
Jose-Angel Conchello; Carol J. Cogswell; Tony Wilson; Thomas G. Brown, Editor(s)

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