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Related Concept Videos

Electron Microscope Tomography and Single-particle Reconstruction01:07

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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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Updated: Mar 15, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
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Contextual High-Throughput 3D Volume Electron Microscopy Data Acquisition Using Artificial Intelligence.

Tereza Hurník Konečná1, Radek Jančík1, Daniela Slamková1

  • 1Materials and Structural Analysis Division, Thermo Fisher Scientific, Vlastimila Pecha 1282/12, Brno 62700, Czech Republic.

Microscopy and Microanalysis : the Official Journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|March 13, 2026
PubMed
Summary
This summary is machine-generated.

Adaptive Scanning uses AI to create masks, enabling targeted high-resolution imaging in 3D volume electron microscopy (vEM). This dynamic-resolution approach significantly reduces acquisition time for large datasets across various samples.

Keywords:
3D electron microscopyFIB-SEMartificial intelligencedeep learningvolumeEM

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Area of Science:

  • Electron Microscopy
  • Artificial Intelligence
  • Bioimaging

Background:

  • Generating large 3D volume electron microscopy (vEM) datasets is time-consuming.
  • High-resolution imaging of extensive biological structures presents significant challenges.

Purpose of the Study:

  • To develop an AI-driven method to accelerate 3D vEM data acquisition.
  • To introduce a dynamic-resolution scanning strategy for efficient vEM imaging.

Main Methods:

  • Implemented Artificial Intelligence (AI) algorithms to generate region-of-interest masks.
  • Developed an Adaptive Scanning technique for dynamic-resolution data capture.
  • Applied the method across diverse biological samples, including brains, parasites, cells, and plants.

Main Results:

  • Adaptive Scanning significantly reduced data acquisition times.
  • The method achieved high-resolution imaging of targeted structures while capturing surrounding areas at lower resolution.
  • Demonstrated sample agnosticism, proving compatibility with various organisms and tissues.

Conclusions:

  • The multiresolution scanning strategy enhances throughput for 3D vEM.
  • This approach offers potential time savings of up to twofold or more.
  • Enables more efficient, cost-effective generation of larger vEM datasets for increased statistical power.