SIMToolbox

SIMToolbox is an open-source software tool with a user-friendly graphical interface designed for processing 2D and 3D data acquired by structured illumination microscopy (SIM). It supports both optical sectioning and super-resolution applications and includes maximum a posteriori probability image estimation (MAP-SIM), an alternative method for reconstruction of structured illumination images. MAP-SIM can potentially reduce reconstruction artifacts caused by refractive index mismatch within the sample and illumination imperfections.

Topic

Biological imaging;Imaging;Light microscopy

Detail

  • Operation: Microscope image visualisation;Image analysis

  • Software interface: Library

  • Language: MATLAB

  • License: -

  • Cost: Free

  • Version name: -

  • Credit: UCCS center for the BioFrontiers Institute and by the CTU, a SCIEX fellowship.

  • Input: -

  • Output: -

  • Contact: lukestom@fel.cvut.cz

  • Collection: -

  • Maturity: -

Publications

  • SIMToolbox: a MATLAB toolbox for structured illumination fluorescence microscopy.
  • Křížek P, et al. SIMToolbox: a MATLAB toolbox for structured illumination fluorescence microscopy. SIMToolbox: a MATLAB toolbox for structured illumination fluorescence microscopy. 2016; 32:318-20. doi: 10.1093/bioinformatics/btv576
  • https://doi.org/10.1093/bioinformatics/btv576
  • PMID: 26446133
  • PMC: -
  • Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction.
  • Pospíšil J, et al. Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction. Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction. 2019; 8:(unknown pages). doi: 10.1093/gigascience/giy126
  • https://doi.org/10.1093/gigascience/giy126
  • PMID: 30351383
  • PMC: PMC6325271
  • Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation.
  • Lukeš T, et al. Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation. Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation. 2014; 22:29805-17. doi: 10.1364/OE.22.029805
  • https://doi.org/10.1364/OE.22.029805
  • PMID: 25606910
  • PMC: -

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