Related Experiment Video
Updated: May 15, 2026
Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
Published on: November 17, 2016
An automated workflow for fungal cell counting, cell size and data analysis: enhancing throughput and accuracy with
Jakob Scheler1,2, Dominik Kutra3, Vincent Beliveau4
1Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Tyrol, Austria. jakob.scheler@i-med.ac.at.
Background:
The development of filamentous fungal cells from spore to mature mycelium is influenced by a myriad of environmental conditions. Traditional methods for quantifying various fungal cell morphologies in liquid media via microscopy are labor-intensive and prone to user-dependent variability.
Methods:
This study addresses these challenges by introducing a streamlined workflow for fungal cell analysis, utilizing ilastik-based image segmentation and Python for fast data preparation and analysis. The goal is to offer a user-friendly method for counting and analyzing different fungal cell morphologies and their sizes that is free of charge and accessible to users with minimal programming experience.
Results:
The presented workflow significantly reduces the time required to determine cell developmental stages from microscopy images. It enables rapid results, as compared to manual counting. It also minimizes inter-user variability, enhancing consistency across analyses. It provides a high-throughput, automated solution for fungal cell analysis allowing users to process hundreds of images (n = 48-438) for analysis in a short time period (9-56 min).
Conclusion:
This approach shows great potential for accelerating research and improving data reliability in biological studies. Furthermore, it provides laboratories in resource limited settings with a free to use solution.
