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Optimization of 3D Immunofluorescence Analysis and Visualization Using IMARIS and MeshLab.

Zulzikry Hafiz Abu Bakar1, Jean-Pierre Bellier2, Wan Zurinah Wan Ngah1

  • 1Medical Innovation Research Center, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu 520-2192, Japan.

Cells
|January 21, 2023
PubMed
Summary

Three-dimensional (3D) colocalization analysis offers enhanced precision. This study presents a novel method using MeshLab to simplify complex 3D models, maintaining quality for accurate spatial colocalization determination.

Keywords:
3DIMARISMeshLabcolocalization analysisdecimationsimplification

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Area of Science:

  • Cell Biology
  • Microscopy
  • Image Analysis

Background:

  • Three-dimensional (3D) colocalization analysis provides greater precision than 2D methods.
  • Rendering 3D colocalization models can result in high polygon counts, complicating analysis.
  • Efficient simplification of these complex models is crucial for practical application.

Purpose of the Study:

  • To develop and evaluate a method for simplifying complex 3D colocalization models.
  • To assess the effectiveness of different simplification algorithms in maintaining model quality.
  • To identify optimal visualization techniques for 3D colocalization analysis.

Main Methods:

  • Acquisition of stacked images using double immunofluorescence staining for FtMt/LC3.
  • Rendering of 3D colocalization models using IMARIS.
  • Simplification and decimation of 3D models using MeshLab, including evaluation of simplification algorithms and shaders.

Main Results:

  • The Quadric Edge Collapse Decimation (QECD) algorithm was identified as the most effective for reducing model complexity without quality loss.
  • MeshLab's x-ray shader was found to be beneficial for visualizing spatial colocalization.
  • Simplified 3D models accurately represent colocalization data.

Conclusions:

  • A novel and reliable method for rendering simplified 3D colocalization models has been established.
  • The QECD method and x-ray shader offer practical solutions for complex 3D colocalization analysis.
  • This approach enhances the accuracy and efficiency of quantifying colocalization in biological samples.