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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: Apr 27, 2026

Isotropic Light-Sheet Microscopy and Automated Cell Lineage Analyses to Catalogue Caenorhabditis elegans Embryogenesis with Subcellular Resolution

Isotropic Light-Sheet Microscopy and Automated Cell Lineage Analyses to Catalogue Caenorhabditis elegans Embryogenesis with Subcellular Resolution

Published on: June 6, 2019

Open-source solutions for SPIMage processing.

Christopher Schmied¹, Evangelia Stamataki¹, Pavel Tomancak¹

¹Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

Methods in Cell Biology

|June 30, 2014

Summary

This summary is machine-generated.

This study presents practical, open-source recipes for processing selective plane illumination microscopy (SPIM) data. These methods simplify complex image registration, fusion, and deconvolution for biologists using SPIM imaging.

Keywords:

Bead-based registration Fiji Image processing Light sheet microscopy Lightsheet Z.1 Multiview OpenSPIM SPIM Time-lapse

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Isotropic Light-Sheet Microscopy and Automated Cell Lineage Analyses to Catalogue Caenorhabditis elegans Embryogenesis with Subcellular Resolution

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Published on: August 15, 2014

Area of Science:

Biotechnology
Microscopy
Bioimaging

Background:

Light sheet microscopy offers high-resolution, low-damage visualization of dynamic biological processes.
Selective plane illumination microscopy (SPIM) enables whole-embryo imaging but requires extensive post-processing.
Existing SPIM data processing workflows can be complex for biologists.

Purpose of the Study:

To provide accessible, practical protocols for SPIM data post-processing.
To demystify the underlying principles of SPIM image analysis algorithms.
To enable researchers to effectively process their own SPIM datasets.

Main Methods:

Development of step-by-step recipes for SPIM data registration and fusion.
Application of deconvolution and time-lapse registration techniques.
Utilizing publicly available, open-source software tools for image analysis.

Main Results:

A set of user-friendly protocols for SPIM data processing is presented.
Explanation of SPIM image processing algorithms in plain language.
Protocols are validated for both commercial (Zeiss Lightsheet Z.1) and open-access (OpenSPIM) platforms.

Conclusions:

The provided recipes simplify complex SPIM data analysis for biologists.
Informed parameter tuning is facilitated through clear algorithm explanations.
These protocols enhance the accessibility and utility of SPIM imaging for biological research.