%0 Generic
%A Kalisvaart, Dylan
%A Cnossen, Jelmer
%A Hung, Shih-Te
%A Stallinga, S. (Sjoerd)
%A Verhaegen, Michel
%A Smith, Carlas
%D 2022
%T Data underlying the publication: Precision in iterative modulation enhanced single-molecule localization microscopy
%U https://data.4tu.nl/articles/dataset/Data_underlying_the_publication_Precision_in_iterative_modulation_enhanced_single-molecule_localization_microscopy/19786735/1
%R 10.4121/19786735.v1
%K Super-resolution microscopy
%K Single Molecule Localization
%K Single Molecule Localization Microscopy
%K Iterative Localization Microscopy
%K Modulation Enhanced Localization Microscopy
%K Precision
%K Cramer-Rao Lower Bound
%K Van Trees Inequality
%X <h2>General information</h2>
<p>This simulation data belongs to the article:</p>
<p>Precision in iterative modulation enhanced single-molecule localization microscopy</p>
<p>DOI: <sub><a href="https://doi.org/10.1016/j.bpj.2022.05.027" target="_blank">https://doi.org/10.1016/j.bpj.2022.05.027</a></sub></p>
<p>This information is also available in README.txt, included in this repository.</p>
<h2>Data availability</h2>
<p>The simulation code underlying the article can be found at:</p>
<p><sub><a href="https://github.com/qnano/iterative-localization" target="_blank">https://github.com/qnano/iterative-localization</a></sub></p>
<h2>Data description</h2>
<p>The simulation data in this repository, consisting of .npy files, is contained in several .zip files. The title of the .zip files describes which quantity is contained in it. </p>
<p>Specifically:</p>
<ul>
  <li><em>CRLBxI.zip</em>: Cramér-Rao lower bound, computed over all iterations in the fixed photon budget scenario.</li>
  <li><em>CRLBxM.zip</em>: Approximation of the Cramér-Rao lower bound in the fixed photon budget scenario, from Balzarotti et al. (2017). Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes. Science 355:606–612. </li>
  <li><em>FT-I.zip</em>: Fisher information matrix in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-J.zip</em>: Bayesian information matrix in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-JT.zip</em>: Analytical approximation of the Bayesian information matrix in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-mod.zip</em>: Fraction of the photon budget used in each iteration in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-modT.zip</em>: Fraction of the photon budget used in each iteration assuming the analytical approximation of the VTI, in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-smp.zip</em>: Regions of interest in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-theta.zip</em>: Ground truth estimand values after subpixel randomization in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-thetaMAP.zip</em>: Maximum a posteriori (MAP) estimated parameter values in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-VTIx.zip</em>: Van Trees inequality (VTI) in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>FT-VTIxT.zip</em>: Analytical approximation of the VTI in the fixed imaging time and fixed illumination intensity scenario.</li>
  <li><em>I.zip</em>: Fisher information matrix in the fixed photon budget scenario.</li>
  <li><em>J.zip</em>: Bayesian information matrix in the fixed photon budget scenario.</li>
  <li><em>JT.zip</em>: Analytical approximation of the Bayesian information matrix in the fixed photon budget scenario.</li>
  <li><em>smp.zip</em>: Regions of interest in the fixed photon budget scenario.</li>
  <li><em>theta.zip</em>: Ground truth estimand values after subpixel randomization in the fixed photon budget scenario.</li>
  <li><em>thetaMAP.zip</em>: Maximum a posteriori (MAP) estimated parameter values in the fixed photon budget scenario.</li>
  <li><em>VTIx.zip</em>: Van Trees inequality (VTI) in the fixed photon budget scenario.</li>
  <li><em>VTIxT.zip</em>: Analytical approximation of the VTI in the fixed photon budget scenario.</li>
</ul>
<p>If you want to access all the data, including (raw) quantities that are not directly used to compute the results shown in the article, download <em>SimData.zip</em>. <em>SimData.zip</em> contains all data from individual .zip-files, combined for your convenience. Alternatively, you can download all individual .zip-files.</p>
<p>Within the .zip folders, the title of the data contains the simulation parameters it was obtained from. The data titles follow the following format (where the brackets [...] indicate variables):</p>
<p><em>[prefix]</em>-iter-<em>[parameter itermax]</em>-thetaI-<em>[parameter theta_I]</em>-m-<em>[parameter 100*m]</em>-alpha-<em>[parameter 100*alpha]</em>-thetab-<em>[parameter theta_b]</em>.npy</p>
<p>The variables are defined as follows:</p>
<ul>
  <li><em>[prefix]</em>: Quantity name, as in the .zip title (e.g. CRLBxI, CRLBxM).</li>
  <li><em>[parameter itermax]</em>: Parameter itermax, i.e. the amount of imeSMLM iterations, that was used in simulation.</li>
  <li><em>[parameter theta_I]</em>: Parameter theta_I, i.e. the expected signal photon intensity over all iterations under maximum illumination (photons), that was used in simulation.</li>
  <li><em>[parameter 100*m]</em>: Parameter m, i.e. the modulation contrast of the illumination patterns, that was used in simulation. Values were multiplied by 100 in the title only, to avoid commas in the title.</li>
  <li><em>[parameter 100*alpha]</em>: Parameter alpha, i.e. the aggressiveness parameter/the amount of standard deviations between the emitter estimate and a pattern minimum, that was used in simulation. Values were multiplied by 100 in the title only, to avoid commas in the title.</li>
  <li><em>[parameter theta_b]</em>: Parameter theta_b, i.e. the expected background photon count per pixel, assumed to be uniform over the region of interest (photons/pixel), that was used in simulation.</li>
</ul>
<p>For example, the file <em>VTIx-iter-3-thetaI-2000-m-95-alpha-300-thetab-8.npy</em> contains the simulated VTI values of an imeSMLM experiment in the fixed photon budget scenario with 3 iterations, an expected photon budget of 2000 photons, a modulation contrast of 0.95, an aggressiveness parameter of 3 and an expected background of 8 photons/pixel.</p>
<p>The reference table <em>Datasets.xlsx</em> describes which simulation parameters are used in each simulation. It also contains an overview of which datasets are used in each of the figures in the article.</p>
<h2>Using existing data</h2>
<p>This section describes how to use the simulation data in this repository to reproduce results.</p>
<p>1. Download <em>Datasets.xlsx </em>and place it in the directory "/iterative_localization/". This file describes which simulation parameters are used in each simulation. It also contains an overview of which datasets are used in each of the figures in the article.</p>
<p>2. Download the appropriate (raw and processed) simulation data. Specifically:</p>
<ul>
  <li>If you intend to only reproduce the results and want to use the minimum amount of data to do so, download the following data and extract it to the directory "/iterative_localization/SimData/":</li>
</ul>
<ol>
  <li><em>CRLBxI.zip</em></li>
  <li><em>CRLBxM.zip</em></li>
  <li><em>FT-J.zip</em></li>
  <li><em>FT-mod.zip</em></li>
  <li><em>FT-modT.zip</em></li>
  <li><em>FT-smp.zip</em></li>
  <li><em>FT-theta.zip</em></li>
  <li><em>FT-thetaMAP.zip</em></li>
  <li><em>FT-VTIx.zip</em></li>
  <li><em>FT-VTIxT.zip</em></li>
  <li><em>J.zip</em></li>
  <li><em>smp.zip</em></li>
  <li><em>theta.zip</em></li>
  <li><em>thetaMAP.zip</em></li>
  <li><em>VTIx.zip</em></li>
  <li><em>VTIxT.zip</em></li>
</ol>
<ul>
  <li>If you want to access all the data, including (raw) quantities that are not directly used to compute the results shown in the article, download <em>SimData.zip</em> and extract it to the directory "/iterative_localization/SimData/". <em>SimData.zip</em> contains all data from individual .zip-files, combined for your convenience. Alternatively, you can download all individual .zip-files and extract them to the directory "/iterative_localization/SimData/".</li>
</ul>
%I 4TU.ResearchData