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Imaging Biological Samples with Optical Microscopy

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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.
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Updated: Jun 19, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Modular training resources for bioimage analysis.

Christian Tischer¹, Antonio Zaccaria Politi², Tim-Oliver Buchholz³

¹Data Science Centre, European Molecular Biology Laboratory, Heidelberg, Germany.

Journal of Microscopy

|June 18, 2026

Summary

This summary is machine-generated.

This study introduces an open-access bioimage analysis training resource to help life scientists handle complex microscopy data. The modular material supports reproducible analysis and is available on a public repository for community contributions.

Keywords:

image analysis microscopy open‐access teaching

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Area of Science:

Life Sciences
Microscopy
Bioimage Analysis

Background:

Modern microscopy generates vast and complex imaging data.
Extracting accurate scientific information requires specialized bioimage analysis expertise.
There is a need for accessible training resources in bioimage analysis for life scientists.

Purpose of the Study:

To develop and provide an open-access training resource for bioimage analysis.
To assist trainers in designing and conducting bioimage analysis courses for life scientists.
To facilitate the dissemination of essential bioimage analysis skills.

Main Methods:

Developed a modular, open-access training resource.
Included concise modules covering specific bioimage analysis topics.
Provided activities using real microscopy images and popular software (ImageJ, Python).
Hosted the resource on a public software repository for community contributions.

Main Results:

The resource is modular, with each module focusing on a specific topic.
Activities are designed for various popular software packages like ImageJ and Python.
The training material is hosted on a public repository, encouraging community input.
The resource has been utilized in numerous courses over the past three years and is continuously improved.

Conclusions:

The developed resource effectively supports the training of life scientists in bioimage analysis.
The open-access and modular nature of the resource promotes widespread adoption and continuous improvement.
Community contributions to the public repository enhance the resource's utility and relevance.