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Related Concept Videos

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been developed.
Overview of Electron Microscopy01:25

Overview of Electron Microscopy

The wavelengths of visible light ultimately limit the maximum theoretical resolution of images created by light microscopes. Most light microscopes can only magnify 1000X, and a few can magnify up to 1500X. Electrons, like electromagnetic radiation, can behave like waves, but with wavelengths of 0.005 nm, they produce significantly greater resolution up to 0.05 nm as compared to 500 nm for visible light. An electron microscope (EM) can create a sharp image that is magnified up to 2,000,000X.
Electron Microscope Tomography and Single-particle Reconstruction01:07

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.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...

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Updated: May 19, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
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Deep Learning Enables Automated Segmentation and Quantification of Ultrastructure from Transmission Electron

Anqi Zou1, Winston Tan2, Jiayi Ji2

  • 1Computational Biomedicine Section, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.

Biorxiv : the Preprint Server for Biology
|April 27, 2026
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Summary
This summary is machine-generated.

TEAMKidney, a deep learning tool, automates kidney ultrastructure analysis from transmission electron microscopy (TEM) images. It accurately measures structures, reducing manual labor and improving consistency in research and clinical diagnosis.

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Area of Science:

  • Biomedical imaging
  • Computational pathology
  • Renal pathology

Background:

  • Transmission electron microscopy (TEM) is vital for subcellular ultrastructure analysis in clinical diagnosis and research.
  • Current TEM data analysis is labor-intensive and inconsistent due to a lack of computational methods.
  • Accurate measurement of complex kidney ultrastructures is challenging.

Purpose of the Study:

  • To develop a deep learning framework (TEAMKidney) for accurate and scalable measurement of kidney ultrastructures in TEM images.
  • To address challenges in TEM data analysis, including limited labeled data and segmentation accuracy.
  • To apply TEAMKidney to identify disease-associated changes in human and animal kidney ultrastructures.

Main Methods:

  • Collected 12,991 TEM images from human kidney diseases and animal models.
  • Employed a self-training semantic segmentation stage combined with a TEM-tailored panoptic segmentation model.
  • Validated the framework on human and animal TEM images, comparing results with expert measurements.

Main Results:

  • TEAMKidney accurately measures kidney ultrastructures across species, magnifications, and platforms.
  • The framework successfully identified disease-associated changes in glomerular basement membrane and podocyte foot processes.
  • TEAMKidney outperformed existing tools and showed close agreement with expert pathological measurements.

Conclusions:

  • Deep learning framework TEAMKidney significantly reduces the burden of TEM image analysis.
  • TEAMKidney offers expert-level accuracy for measuring kidney ultrastructures, aiding clinical pathology and biomedical research.
  • This approach enhances consistency and scalability in ultrastructural analysis.