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Related Experiment Video

Updated: Mar 11, 2026

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Published on: November 17, 2016

Quantitating the cell: turning images into numbers with ImageJ.

Ellen T Arena^1,2, Curtis T Rueden², Mark C Hiner²

¹Morgridge Institute for Research, Madison, WI, USA.

Wiley Interdisciplinary Reviews. Developmental Biology

|December 3, 2016

Summary

ImageJ, an open-source software, offers powerful image processing for biologists. This review highlights key ImageJ tools for quantitative biological imaging, enhancing cell and developmental biology research.

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Last Updated: Mar 11, 2026

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

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Area of Science:

Biological Imaging
Cell Biology
Developmental Biology

Background:

Light microscopy has significantly advanced biological research, especially in cell and developmental biology.
Digital imaging and computational analysis have enabled quantitative analysis of dynamic biological phenomena.
Biologists require accessible image processing routines and intuitive software for quantitative imaging.

Purpose of the Study:

To review prominent image processing approaches in ImageJ relevant to biological imaging.
To illustrate the functionality of ImageJ and other open-source image analysis software.
To address the need for accessible and extensible image processing solutions in bioimaging.

Main Methods:

Overview of image processing techniques available in ImageJ.
Focus on algorithms applicable to light microscopy and biological samples.
Discussion of open-source software solutions for bioimage analysis.

Main Results:

ImageJ provides a powerful, accessible platform for quantitative biological image analysis.
Open-source software like ImageJ overcomes limitations of proprietary tools.
Numerous algorithms, both novel and adapted, are available within ImageJ for diverse imaging needs.

Conclusions:

ImageJ is a crucial tool for modern biological research, enabling quantitative analysis of complex imaging data.
Open-source bioimaging software democratizes access to advanced image processing capabilities.
Continued development and utilization of ImageJ will further drive discoveries in cell and developmental biology.