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Related Concept Videos

Two-Dimensional Microscopy in Microbiology01:29

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Two-dimensional (2D) microscopy encompasses a range of optical techniques that capture images within a single focal plane, offering detailed representations of microscopic structures. These techniques are essential in biological and medical research, enabling the visualization of cellular and subcellular structures with different levels of contrast and specificity.There are several major types of 2D microscopy, each with strengths and applications.Bright-Field MicroscopyBright-field microscopy...
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Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
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Related Experiment Video

Updated: Feb 6, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
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Toward quantitative three-dimensional microvascular networks segmentation with multiview light-sheet fluorescence

Pol Kennel1, Lise Teyssedre2, Julien Colombelli3

  • 1Toulouse University, CNRS, INPT, UPS, Institute of Fluid Mechanics of Toulouse, Toulouse, France.

Journal of Biomedical Optics
|August 19, 2018
PubMed
Summary

Reliable 3-D vessel segmentation from large tissue volumes is crucial for understanding biological and medical issues. Light-sheet fluorescence microscopy (LSFM) combined with deconvolution and registration offers accurate microvascular network reconstruction for perfusion modeling.

Keywords:
light sheetmicrovasculaturemultiview imagingpermeabilityvascular network

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Area of Science:

  • Biology and Medicine
  • Microscopy and Imaging
  • Bioengineering

Background:

  • Three-dimensional (3-D) imaging of microvascular networks is vital for studying structural, functional, developmental, and pathological processes.
  • Light-sheet fluorescence microscopy (LSFM) is emerging as a powerful technique for large-scale tissue imaging, offering operational solutions.

Purpose of the Study:

  • To develop and validate a reliable image analysis workflow for accurate vessel segmentation in large tissue volumes using LSFM data.
  • To assess the impact of multiview deconvolution on the quantitative accuracy of reconstructed microvascular networks.

Main Methods:

  • Utilized a multiview deconvolution image processing workflow on large-scale Light-sheet fluorescence microscopy (LSFM) data.
  • Systematically analyzed various low-level and high-level metrics to evaluate the accuracy of the reconstructed vascular network.
  • Investigated the sensitivity of structural and functional metrics to image processing parameters, including the number of views.

Main Results:

  • Low-level structural metrics showed sensitivity to isotropic imaging enhancement achieved with more views.
  • High-level functional metrics, such as perfusion permeability, demonstrated less sensitivity to the number of views.
  • Combining deconvolution and registration with a limited number of views proved sufficient for reliable quantitative 3-D vessel segmentation.

Conclusions:

  • A robust image analysis workflow combining deconvolution and registration enables accurate 3-D microvascular network segmentation from LSFM data.
  • The developed method supports quantitative analysis of vascular structures and is suitable for applications like perfusion modeling.