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Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
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Related Experiment Video

Updated: Jun 12, 2026

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)
11:57

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

Published on: December 1, 2016

Polarization 3D reconstruction based on multi-exposure fusion.

Hui Du, Zhiqiang Liu, Yudong Cai

    Optics Express
    |June 11, 2026
    PubMed
    Summary

    This study introduces a new 3D reconstruction technique using polarization imaging. The method significantly reduces noise and improves the accuracy of 3D surface details and normals, leading to better reconstructions.

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    Determining 3D Flow Fields via Multi-camera Light Field Imaging
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    Determining 3D Flow Fields via Multi-camera Light Field Imaging

    Published on: March 6, 2013

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    Last Updated: Jun 12, 2026

    Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)
    11:57

    Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

    Published on: December 1, 2016

    Determining 3D Flow Fields via Multi-camera Light Field Imaging
    14:25

    Determining 3D Flow Fields via Multi-camera Light Field Imaging

    Published on: March 6, 2013

    Area of Science:

    • Computer Vision
    • Optical Metrology
    • 3D Imaging

    Background:

    • Polarization-based 3D reconstruction provides high precision and cost-effectiveness.
    • Existing methods often neglect noise suppression during image acquisition, impacting reconstruction quality.

    Purpose of the Study:

    • To develop an improved polarization-based 3D reconstruction method.
    • To address noise and distortion issues in image acquisition for enhanced 3D accuracy.

    Main Methods:

    • A pixel-wise multi-exposure fusion approach was employed.
    • Optimal responses within the linear camera curve were selected to minimize photon noise and nonlinear distortions.
    • A highlight correction strategy was implemented to reduce specular-gradient errors.

    Main Results:

    • The proposed method effectively suppresses Gaussian and systematic noise.
    • Polarization accuracy was enhanced, leading to more precise surface normals.
    • 3D reconstruction details were significantly clearer, with a 14.3% reduction in surface normal RMSE compared to traditional methods.

    Conclusions:

    • The developed method offers superior noise suppression for polarization-based 3D reconstruction.
    • It achieves higher accuracy in surface normal estimation and overall 3D model quality.
    • The technique provides a more robust and precise solution for detailed 3D surface reconstruction.