Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Calorie restriction modulates beta cell IP<sub>3</sub>R activity to regulate Ca<sup>2+</sup> homeostasis and cell network connectivity.

Cell calcium·2026
Same author

Disruption to TFEB signaling and autophagy in newly formed oligodendrocytes leads to aberrant generation of CNS myelin.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Therapeutic targeting of fibrin-microglia interactions ameliorates Alzheimer's disease-related hyperexcitability and brain network dysfunction.

bioRxiv : the preprint server for biology·2026
Same author

Resilience to neuronal hyperactivity and restoration of the neuroimmune interactome by blocking fibrin-induced microglia activation in Alzheimers disease.

bioRxiv : the preprint server for biology·2026
Same author

Adam9-deficient retinal pigment epithelium pseudopods maintain photoreceptor outer segment renewal despite subretinal space expansion.

The Journal of clinical investigation·2026
Same author

ER remodelling is a feature of ageing and depends on ER-phagy.

Nature cell biology·2026

Related Experiment Video

Updated: Jul 6, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Segmentation of electron tomographic data sets using fuzzy set theory principles.

Edgar Garduño1, Mona Wong-Barnum, Niels Volkmann

  • 1Depto. Ciencias de la Computación, Instituto de Investigaciones en Matermáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Circuito Escolar S/N, Cd. Universitaria, C.P. 04510, Mexico City, Mexico. edgargar@ieee.org

Journal of Structural Biology
|March 25, 2008
PubMed
Summary
This summary is machine-generated.

Fuzzy segmentation effectively separates structures in noisy electron tomography data. This method shows promise for analyzing biological samples like spiny dendrites, offering an alternative to manual segmentation.

More Related Videos

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Related Experiment Videos

Last Updated: Jul 6, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Area of Science:

  • Biophysics
  • Neuroscience
  • Microscopy

Background:

  • Electron tomography (ET) reconstructions are often degraded by noise and artifacts.
  • Manual segmentation remains the primary method for analyzing ET data, despite its limitations.
  • Existing automated methods struggle with low signal-to-noise ratios common in ET.

Purpose of the Study:

  • To evaluate the efficacy of fuzzy segmentation for analyzing noisy electron tomographic reconstructions.
  • To assess the performance of fuzzy segmentation on biological samples, specifically spiny dendrites.

Main Methods:

  • Applied a fuzzy logic-based segmentation algorithm to electron tomographic reconstructions.
  • Tested the algorithm on selectively stained, plastic-embedded spiny dendrites.

Main Results:

  • The fuzzy segmentation algorithm successfully separated meaningful regions in noisy ET data.
  • The method demonstrated encouraging results within the tested scope of spiny dendrite analysis.
  • Fuzzy segmentation offers a viable alternative to manual segmentation for certain ET applications.

Conclusions:

  • Fuzzy segmentation is a promising approach for analyzing complex, noisy electron tomography data.
  • This method can aid in the detailed structural analysis of biological specimens like neuronal dendrites.
  • Further development could expand the application of fuzzy segmentation in structural biology and neuroscience.