Revision as of 17:07, 30 March 2018 by Ehrenfeu (talk | contribs) (Preliminary instructions for the beads method, add citation links)

NoiSee (ImageJ)
Author Niko Ehrenfeuchter
Update site NoiSee
Maintainer Niko Ehrenfeuchter
Source on GitHub
Initial release 2018
Development status active
Category Analysis

NoiSee - An easy-to-use ImageJ macro for measuring SNR (signal-to-noise ratio) of light microscopes.


Enable the corresponding update site and restart Fiji.


Bead Method

  • Start Fiji
  • Type “NoiSee” in the quick search bar, select “Bead Analysis” and click “Run”
  • In the parameters dialog
    • Specify the path to the time lapse bead image.
      • All result files generated by NoiSee will be placed in a new sub-folder located in the same directory as the input image.
    • Specify the diameter of the beads in pixels. NoiSee uses the “Find Maxima” function to automatically detect beads above a certain intensity threshold that needs to be roughly estimated. Starting values for this estimate depending on the detector type used, e.g. 50 for PMTs, 10 for Hybrid detectors in photon counting mode or 500 for camera based systems.
      • If not all beads are identified the estimate should be lower.
      • If peaks other than beads are identified the estimate should be higher.
    • Note: While NoiSee tries to exclude hot pixels and overexposed beads, these would ideally be already avoided during imaging.
    • Choose whether you wish to create kymographs. We recommend to do so as they are useful to inspect sample drift and bleaching.
    • NoiSee can further save additional data (individual measurements per bead) as txt-files.
    • All images and plots created by NoiSee can optionally be saved in a PDF report.
    • ROIs used for measurements are available from the ROI manger and can additionally be visualized as extra images.
    • Press “OK” and wait for NoiSee to finish its calculations.
    • A summary of all NoiSee results is automatically saved as a txt-file.



Please note that NoiSee is based on a publication. If you use it for related research please be so kind to cite our work:

Alexia Ferrand, Kai D Schleicher, Nikolaus Ehrenfeuchter, Wolf Heusermann, Oliver Biehlmaier: Signal-to-Noise ratio made easy: A tool to assess your confocal performance bioRxiv 291500.