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Proceedings Article

Comparison of estimation algorithms in single-molecule localization

[+] Author Affiliations
Anish V. Abraham

The Univ. of Texas at Dallas, (USA) and The Univ. of Texas Southwestern Medical Ctr. at Dallas (USA)

Sripad Ram, E. Sally Ward

The Univ. of Texas Southwestern Medical Ctr. at Dallas (USA)

Jerry Chao

The Univ. of Texas at Dallas (USA) and The Univ. of Texas Southwestern Medical Ctr. at Dallas (USA)

Raimund J. Ober

The Univ. of Texas Southwestern Medical Ctr. at Dallas (USA) and The Univ. of Texas at Dallas (USA)

Proc. SPIE 7570, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVII, 757004 (February 24, 2010); doi:10.1117/12.842178
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From Conference Volume 7570

  • Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVII
  • Jose-Angel Conchello; Carol J. Cogswell; Tony Wilson; Thomas G. Brown
  • San Francisco, California | January 23, 2010

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).

© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Anish V. Abraham ; Sripad Ram ; Jerry Chao ; E. Sally Ward and Raimund J. Ober
"Comparison of estimation algorithms in single-molecule localization", Proc. SPIE 7570, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVII, 757004 (February 24, 2010); doi:10.1117/12.842178; http://dx.doi.org/10.1117/12.842178


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