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Related Experiment Video

Updated: Dec 9, 2025

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

Integration of the ImageJ Ecosystem in the KNIME Analytics Platform.

Christian Dietz¹, Curtis T Rueden², Stefan Helfrich¹

¹KNIME GmbH, Konstanz, Germany.

Frontiers in Computer Science

|September 9, 2020

Summary

This summary is machine-generated.

This study integrates ImageJ, a popular bioimage analysis tool, with KNIME Analytics Platform. This integration enables reproducible, scalable, and extensible scientific image analysis workflows.

Keywords:

Bioimaging Fiji ImageJ KNIME computational workflows image analysis interoperability open-source

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Last Updated: Dec 9, 2025

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Area of Science:

Bioimage analysis
Computational biology
Scientific image processing

Background:

Open-source software is crucial for scientific image analysis due to evolving imaging technologies.
Integrating diverse computational tools (image processing, machine learning, statistics) is challenging but necessary for complex analyses.
Existing tools like ImageJ offer flexibility but lack robust workflow integration for end-to-end bioimage analysis.

Purpose of the Study:

To address the lack of integration in bioimage analysis tools.
To present the KNIME Image Processing extension as a solution for creating reproducible and scalable workflows.
To demonstrate how to leverage the ImageJ ecosystem within the KNIME Analytics Platform.

Main Methods:

Integration of the ImageJ ecosystem into KNIME Analytics Platform via the KNIME Image Processing extension.
Development of user-friendly workflows for complex, end-to-end image analysis tasks.
Utilizing KNIME's platform-agnostic capabilities for heterogeneous data handling.

Main Results:

Enables the creation of robust and extensible image analysis workflows.
Facilitates the integration of a diverse range of analysis tools within a single platform.
Supports reproducible and scalable scientific research in bioimage analysis.

Conclusions:

The KNIME Image Processing extension successfully integrates ImageJ into KNIME Analytics Platform.
This integration empowers researchers to build complex, reproducible, and scalable bioimage analysis workflows.
Leveraging the ImageJ ecosystem within KNIME offers significant benefits for scientific discovery.