Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Imaging Biological Samples with Optical Microscopy

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

SAMJ: fast image annotation on ImageJ/Fiji via segment anything model.

Nature communications·2026

Same author

Search, organize, aggregate and share image data with BioFile Finder (BFF).

Nature methods·2026

Same author

Remotely accessible optical microscopy education through a wide (and global) lens.

Journal of microscopy·2026

Same author

EpiCure (Epithelial Curation): a versatile and handy tool for curation of epithelial segmentation.

bioRxiv : the preprint server for biology·2026

Same author

Introducing ARONG, A 3D Reconstruction Method for Highly Deformed Histology.

Journal of imaging informatics in medicine·2026

Same author

FLIM quality metric visualization as a means to validate consistency across large-area non-homogeneous FLIM datasets.

Methods and applications in fluorescence·2026

Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026

Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026

Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026

Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026

Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026

Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 12, 2026

Clock Scan Protocol for Image Analysis: ImageJ Plugins

Clock Scan Protocol for Image Analysis: ImageJ Plugins

Published on: June 19, 2017

ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability.

Mark C Hiner¹, Curtis T Rueden¹, Kevin W Eliceiri^1,2

¹Laboratory for Optical and Computational Instrumentation, Madison, WI 53706, USA.

Bioinformatics (Oxford, England)

|November 1, 2016

Summary

This summary is machine-generated.

ImageJ-MATLAB is a Java library enabling seamless data exchange between MATLAB and ImageJ. This tool enhances image analysis by allowing researchers to leverage the strengths of both platforms for complex tasks.

More Related Videos

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

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Related Experiment Videos

Last Updated: Mar 12, 2026

Clock Scan Protocol for Image Analysis: ImageJ Plugins

Clock Scan Protocol for Image Analysis: ImageJ Plugins

Published on: June 19, 2017

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

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Area of Science:

* Computational Biology
* Image Analysis
* Scientific Software Development

Background:

* ImageJ and MATLAB are powerful, widely-used platforms for scientific image analysis and data processing, respectively.
* Integrating these tools can enhance research capabilities but often requires complex data format conversions.
* A standardized method for bi-directional data translation is needed to streamline workflows.

Purpose of the Study:

* To introduce ImageJ-MATLAB, a Java library designed for seamless interoperability between ImageJ and MATLAB.
* To provide a standard for translating matrix and image data structures between the two environments.
* To empower researchers by enabling them to utilize the optimal tool for specific image-analysis tasks.

Main Methods:

* Development of a lightweight Java library facilitating bi-directional communication.
* Implementation of a standard for data structure translation between MATLAB matrices and ImageJ images.
* Testing with ImageJ 2.0.0-rc-54, Java 1.8.0_66, and MATLAB R2015b.

Main Results:

* Successful establishment of bi-directional data flow between ImageJ and MATLAB.
* A defined standard for matrix-to-image and image-to-matrix data conversion.
* Enhanced flexibility for researchers in choosing analysis tools.

Conclusions:

* ImageJ-MATLAB significantly simplifies the integration of ImageJ and MATLAB for image analysis.
* The library promotes efficient and flexible research workflows by bridging platform specific functionalities.
* This interoperability empowers scientists to select the most appropriate software for their specific image analysis needs.