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[edit] Localisation Microscopy software ("rainSTORM" MATLAB GUI)


We have developed a MATLAB application for Localisation Microscopy image processing, with a simple GUI interface. This application is a set of MATLAB scripts and functions, named rainSTORM, was developed as part of our super-resolution research in collaboration with the Biophysics Group at the National Physical Laboratory.

System Requirements

  1. MATLAB 2009b or more recent is needed to read multi-frame TIF files with reasonable efficiency.
  2. The MATLAB Image Processing Toolbox is needed for a few purposes - e.g. imerode() for background estimation.
  3. The use of the MATLAB Parallel Processing Toolbox is supported, but not required.
  4. Some of the rainSTORM_extras scripts are not functions, and so currently will not be available in a compiled version

Further Reading

Please refer to these publications, and cite as appropriate to acknowledge this software:

  • Rees et al. (2012) Optical Nanoscopy 1:12 (2012), doi:10.1186/2192-2853-1-12 -- Resolution
  • Metcalf et al. (2013) Journal of Visualised Experiments, In Press -- Visual Protocols
  • Rees et al. Journal of Optics (2013) Accepted for a 2013 Special Edition on High Resolution Techniques -- Software
  • Erdelyi et al., Optics Express (2013) 21 (9), 10978–10988 (2013) DOI: 10.1364/OE.21.010978 -- Chromatic Offset Correction

Summary of Software

The rainSTORM software performs the image analysis and visualisation parts of Localisation Microscopy. It reads raw data, typically a TIF stack, and performs (a) Localisation, (b) Quality Control, and (c) Visualisation of the super-resolution image.


  1. Localisation using a "Sparse Segmentation and Least Squares Gaussian Fitting" algorithm (See Journal of Optics paper for a brief review of alternatives)
  2. Quality Control using a range of parameters. Simple, one-parameter Quality Control using the Thompson Precision estimate of each localisation is implemented.
  3. Visualisation using either a "Simple Histogram Image" or a "Jittered Histogram" visualisation. Note that the Jittered Histogram is effectively a form of Adaptive Kernel Density Estimation (see Optical Nanoscopy paper for references).
  4. One-click save of super-resolution images, together with quality-control histograms, and meta-data in a text file.
  5. The resolution of the super-resolved image is also estimated and saved in the text file, using the analysis we presented in: "Blind Assessment of Localisation Microscope Image Resolution," Optical Nanoscopy 1:12, doi:10.1186/2192-2853-1-12

Additional Capabilities:

  1. Image simulation, based on a "test card object." Sample Localisation Microscopy images can be simulated, which is useful for (a) demonstration purposes, and (b) software validation.
  2. X-Y-time scatter plots for particle tracking, and image quality inspection.
  3. Translational drift correction, using fiducial markers tracked by the above method.
  4. Evaluation and correction of chromatic aberration distortion between 2 super-resolved colour channels.
  5. Batch processing.
  6. Preliminary molecule tracking scripts

Included Files

  1. Testcard image for simulation of "crossed line" data for resolution and validation studies
  2. Powerpoint introduction to rainSTORM - by Dr Daniel Metcalf
  3. Development History text file


The rainSTORM software is available for use by any interested groups. It is made available with a LGPL_v3 license (i.e. it is open source software, as specified in its license file). It will shortly be uploaded to a suitable software repository: for now, it is available here. Please contact Dr Eric Rees via email ( to report bugs or irresolvable problems.

Current Version (2.37)

Older Version(s) (2.36)‎

User Guide by Daniel Metcalf:

[edit] Fluorescence Anisotropy: MATLAB video image processing software


This software processes raw microscopy data to obtain fluorescence anisotropy images.

Further Reading

Summary of Software


  1. Limited to a T-type detection using 2 rectangular sub-areas of a single camera.
  2. D.C. camera background subraction.
  3. Image registration
  4. G-factor calibration based on dilute dye solution data
  5. Evaluation of anisotropy images
  6. Generation of anistoropy histograms and statistics


  1. Sample data for alignment
  2. Sample data for G-factor calibration (dilute dye solution in water)
  3. Sample data with given anistropy (dilute dye solution in glycerol)
  4. Sample image data (fluorecent labelled cells)


Preliminary version: (link)

[edit] FRET software developed by the Laser Analytics Group

[edit] MATLAB software for seFRET image processing, and example data


These MATLAB scripts are provided as a guideline for seFRET image processing. They can be used to perform seFRET analysis on the sample data provided in the “Example_Data” folder. They may also be useful for performing seFRET analysis on your own experimental data, or as a starting point for developing a similar method. Please note that these scripts are provided for guidance only, and have no warranty (as specified in the GPL version 3+ license).

Further Reading

These scripts were written to accompany a Springer Protocols book chapter:

  • A quantitative protocol for live cell FRET imaging.

Clemens F. Kaminski, Eric. J. Rees, and Gabriele S. Kaminski Schierle

Chapter 19 in:

Fluorescence Spectroscopy and MicroscopyMethods and Protocols Series: Methods in Molecular Biology, Vol. 1076 Engelborghs, Yves; Visser, Antonie J.W.G. (Eds.) 2013

Our paper on seFRET image processing is:

  • Elder A. D, Domin A., Kaminski Schierle GS, Lindon C, Pines J, Esposito A., Kaminski CF (2009) A quantitative protocol for dynamic measurements of protein interactions by Förster resonance energy transfer-sensitized fluorescence emission. Journal of The Royal Society Interface 6:S59–S81

Summary of Software


  1. Heuristic identification of d.c. background level, and background subtraction
  2. Heuristic identification of usable regions of interest
  3. Evaluation of crosstalk ratios, based on single-dye calibration images
  4. Evaluation of Calibation ratios for FRET normalisation, based on "linker construct" images
  5. Evaluation of normalised FRET images, using sample images
  6. Reporting of normalised FRET statistics
  7. Basic GUI interface for using the software without editing MATLAB scripts

Files Included:

  1. Example data for Crosstalk calibration
  2. Example data for FRET normalisation ratio calibration
  3. Example data for a specimen


Please refer to the README file in the zip folder for more information

Current Version:‎

[edit] IDL Software for seFRET

The group has developed a user friendly software with a graphical user interface for the quantitative analysis of sensitized emission FRET images. Full details on the algorithm, calibration protocols, and example applications are given in the following publication. Please cite this publication when using this software.

[edit] Flat flame calibration burner for temperature and species profile measurements

The group has designed a flat flame burner design that provides ultrastable laminar flames for flame profile measurements. In contrast to McKenna type and other porous plug burner design this burner is ideally suited for seeding with atomic metal species, without risks of "clogging". For full details on the design please see Stable calibration burner.

[edit] Group IT resources

For internal use by the Laser Analytics group, there are further resources available on the CAMTOOLS website:

  1. Log in using Raven
  2. Change to the 'Laser Analytics Group' tab
  3. Navigate to the wiki
  4. Select 'IT resources'

This will list all the major resources and how to use them.

Personal tools
Laser Analytics Group