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Detailed workinar content overview:

  • Short Introduction to Fiji / ImageJ and basic functions
  • Overview over proper scientific image file formats, metadata, bit depth
  • In-depth practical introduction to pre-processing
    • Automatic uneven lighting correction
    • Image filters for improved object detection and noise removal
    • Automatic background subtraction algorithms to reduce unspecific signal
  • Object segmentation with automatic intensity thresholds (semantic segmentation)
  • Individual object labeling (instance segmentation)
  • Optional: Basic insight into some user friendly machine learning plugins in comparison to classical segmentation
  • Optimization of segmentation with post-processing methods
  • Quality control of segmentation results
  • Different basic automatic analyses (object counting, measurements, shapes, intensities)
  • Optional dependent on time: How to deal with 3D data in image analysis
  • Short introduction to macro recording for automation.

All methods are learned hands-on with plenty of practical exercises to get confidence in applying them in your daily work.


GSP / Data Analysis / Hard Skills


The workshop will be held as a virtual live workinar with many hands-on sessions via Zoom.


2 days, each day 9:00 to ~15:30 (max, mostly 15:00 but plan some buffer time)

Main Target Group and Focus:

Life or Natural Scientists starting PhD-student level (1st year) and above. Optimally, some practical imaging experience is an advantage. Nevertheless, independent of the scientific background, everybody is invited to join if interested in the topic.

The course has a very strong focus on fluorescent micrographs! There will be NO analysis of gels or Western blots. Images from immunohistochemical stainings (non-fluorescent) will also be partially discussed, since processing is in parts similar.

Difficulty Level:

The difficulty level is basic to medium and easy to follow in step by step procedures and in-depth explanation of the necessary background to the individual methods. Also scientists with some prior knowledge will still benefit from the methods taught.


  • Computer or Laptop (PC or Mac; supported operating systems: Windows, MacOS and Linux)
  • Stable internet connection
  • Mouse and Headset/Microphone
  • Optimally a webcam
  • Best 2 monitors to watch the workinar on one and do the practical part on the other.
  • Proficiency in handling your computer in general
  • Possibility to install software on your computer (or administrator rights)


During the course we will exclusively work with a customized version of Fiji (ImageJ bundle) Fiji is free of charge, accessible for everybody and open source. Prior software knowledge is not required but might be of advantage.

Registered participants will receive all information regarding software preparation on time before the workshop via email.