Issues in the benchmarking of image analysis algorithms for superresolution microscopy

Shane P. Stahlheber; Alexander R. Small

doi:10.1117/12.2002872

22 February 2013 Issues in the benchmarking of image analysis algorithms for superresolution microscopy

Shane P. Stahlheber, Alexander R. Small

Proceedings Volume 8590, Single Molecule Spectroscopy and Superresolution Imaging VI; 859013 (2013) https://doi.org/10.1117/12.2002872
Event: SPIE BiOS, 2013, San Francisco, California, United States

Abstract

Superresolution localization microscopy requires accurate and precise localization algorithms. We have developed a plugin for ImageJ, called M2LE, which can localize molecules quickly and distinguish between single-molecule and multiple-molecule images using a shape test that requires only a single iteration. Localization is accomplished via a fast maximum-likelihood algorithm that uses the separable property of the Gaussian to independently fit two 1-D Gaussians along the x- and y-directions. To assess the performance of M2LE, we tested the plugin with realistic simulated images of single and multiple molecule images. We first found the optimal shape test parameters that accept most single-molecule images, and then the optimal signal-to-noise cutoff parameter for identifying potential molecules from noise. These two parameters have the greatest impact on what parts of the image go on to be analyzed. Using these optimal parameters, we then assessed (1) the tendency of the algorithm to find molecules from the tail of a point-spread function in high signal-to-noise cases, (2) the effects of regions-of-interest size and overlap tolerances, (3) the ability of shape tests to identify multi-molecule images as a function of molecular separation and ratio of photon counts from two molecules, and (4) the performance of the entire process{the number of molecules identified and their corresponding localization precision and accuracy. These methods and results can be used to identify the optimal M2LE parameters to use for experiments, as well as to compare the performance with other localization microscopy software.

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Shane P. Stahlheber and Alexander R. Small "Issues in the benchmarking of image analysis algorithms for superresolution microscopy", Proc. SPIE 8590, Single Molecule Spectroscopy and Superresolution Imaging VI, 859013 (22 February 2013); https://doi.org/10.1117/12.2002872

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KEYWORDS

Molecules

Photon counting

Microscopy

Molecular photonics

Super resolution

Signal to noise ratio

Point spread functions

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