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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...

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Related Experiment Video

Updated: Jun 4, 2026

Imaging Cleared Intact Biological Systems at a Cellular Level by 3DISCO

Imaging Cleared Intact Biological Systems at a Cellular Level by 3DISCO

Published on: July 7, 2014

Enabling global image data sharing in the life sciences.

Peter Bajcsy¹, Sreenivas Bhattiprolu², Katy Börner³

¹National Institute of Standards and Technology, Gaithersburg, MD, USA.

|March 29, 2025

Summary

This summary is machine-generated.

Making biological and medical image data FAIR (findable, accessible, interoperable, and reusable) is crucial. Public funders must invest in open data resources to support scientists and unlock the value of imaging research.

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Last Updated: Jun 4, 2026

Imaging Cleared Intact Biological Systems at a Cellular Level by 3DISCO

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Published on: July 7, 2014

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Super-Resolution Imaging and Shared Management: A Protocol for Confocal Microscopy with Multiplex Detection

Super-Resolution Imaging and Shared Management: A Protocol for Confocal Microscopy with Multiplex Detection

Published on: February 24, 2026

Area of Science:

Biological imaging
Medical research
Data science

Background:

Vast amounts of valuable biological and medical image data remain inaccessible.
Lack of data accessibility hinders scientific rigor and reuse.
Image data FAIRification is essential for scientific discovery.

Purpose of the Study:

To advocate for public funders' support in making image data FAIR.
To highlight the need for openly accessible, long-term image data storage resources.
To emphasize the importance of national investment in open data infrastructure.

Main Methods:

Global collaboration among image data experts.
Development of common data formats, metadata, and ontologies.
Focus on FAIRification tools and strategies.

Main Results:

Existing international collaborations (Australia, Japan, Europe) are working towards global image data sharing.
Urgent need for openly accessible, long-term operated data storage resources.
Current efforts will be insufficient without increased national investment.

Conclusions:

Public funders must invest in national open data resources for image data.
Federated open data resources are vital for global image data sharing.
Investment in FAIR image data infrastructure maximizes the value of imaging research.