Superresolution fluorescence microscopy techniques such as PALM, STORM, STED, and Structured Illumination
Microscopy (SIM) enable imaging of live cells at nanometer resolution. The common theme in all of these
techniques is that the diffraction limit is circumvented by controlling the states of fluorescent molecules. Although
the samples are labeled very densely (i.e. with spacing much smaller than the Airy distance), not all of the
molecules are emitting at the same time. Consequently, one does not encounter overlapping blurs. In the
deterministic techniques (STED, SIM) the achievable resolution scales as the wavelength of light divided by the
square root of the intensity of a beam used to control the fluorescent state. In the stochastic techniques (PALM,
STORM), the achievable resolution scales as the wavelength of light divided by the square root of the number of
photons collected. Although these limits arise from very different mechanisms (parabolic beam profiles for STED
and SIM, statistics for PALM and STORM), in all cases the resolution scales inversely with the square root of
a measure of the number of photons used in the experiment. We have developed a proof that this relationship
between resolution and photon count is universal to techniques that control the states of fluorophores using
classical light. Our proof encompasses linear and nonlinear optics, as well as computational post-processing
techniques for extracting information beyond the diffraction limit. If there are techniques that can achieve a
more efficient relationship between resolution and photon count, those techniques will require light exhibiting
non-classical correlations.
KEYWORDS: Molecules, Photon counting, Microscopy, Molecular photonics, Super resolution, Signal to noise ratio, Point spread functions, Image analysis, Signal processing, Shape analysis
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.
Superresolution localization microscopy (e.g. PALM, STORM) builds images with sub-wavelength resolution
by analyzing a series of frames containing sparse, non-overlapping single-fluorophore images. A different set
of fluorophores is activated in each frame, and the key parameter controlled by the user is the fraction of
fluorophores activated. Using variational techniques, we show that the optimal activation probability, which
is the result of a tradeoff between speed and accuracy, depends sensitively on two factors: Whether activation
and fluorescent emission are controlled by separate wavelengths or by the same wavelength, and (in the single
wavelength case) the detailed kinetics of the bleaching process. Here our approach is extended to the case of
multi-fluorophore superresolution techniques, where we show that situations that would be ill-suited to singlefluorophore
localization are well-suited to multi-fluorophore localization.
Conference Committee Involvement (2)
Optics Education and Outreach III
19 August 2014 | San Diego, California, United States
Optics Education and Outreach II
12 August 2012 | San Diego, California, United States
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