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Related Experiment Video

Updated: Nov 4, 2025

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

ImageJ and CellProfiler: Complements in Open-Source Bioimage Analysis.

Ellen T A Dobson¹, Beth Cimini², Anna H Klemm³

¹Laboratory for Optical and Computational Instrumentation (LOCI), Center for Quantitative Cell Imaging, University of Wisconsin at Madison, Madison, Wisconsin.

Current Protocols

|May 26, 2021

Summary

This summary is machine-generated.

Integrating ImageJ and CellProfiler enhances bioimage analysis. Combining these platforms offers powerful solutions for cell tracking, morphology studies, and advanced image stitching for improved segmentation.

Keywords:

CellProfiler ImageJ cell tracking image stitching segmentation

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Last Updated: Nov 4, 2025

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A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

Area of Science:

Bioimage analysis
Cell biology
Image processing

Background:

ImageJ and CellProfiler are leading open-source bioimage analysis platforms.
ImageJ excels in single-image analysis, while CellProfiler is suited for large-scale pipelines.
Integrating these platforms can leverage their complementary strengths.

Purpose of the Study:

To demonstrate productive integration of ImageJ and CellProfiler in bioimage analysis workflows.
To showcase pipelines for cell morphology and migration studies using tracking.
To present advanced stitching techniques for large, tiled image sets to enhance segmentation.

Main Methods:

Developed and shared two integrated pipelines combining ImageJ (Fiji/TrackMate) and CellProfiler.
Pipeline 1: Cell morphology and migration tracking in time-lapse datasets.
Pipeline 2: Advanced stitching for whole plate montages to assess segmentation.

Main Results:

Demonstrated effective integration of ImageJ and CellProfiler for specific bioimage analysis tasks.
Showcased improved cell tracking and morphology analysis through combined platform use.
Validated advanced stitching techniques for handling large image datasets and enhancing segmentation.

Conclusions:

Combining ImageJ and CellProfiler in a single workflow offers powerful advantages over using them separately.
Integrated pipelines can address complex bioimage analysis challenges, including cell tracking and segmentation.
Ongoing interoperability development between ImageJ and CellProfiler promises further advancements in bioimage analysis.