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

2.3K
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...
2.3K
Transmission Electron Microscopy01:15

Transmission Electron Microscopy

5.3K
In 1931, physicist Ernst Ruska—building on the idea that magnetic fields can direct an electron beam just as lenses can direct a beam of light in an optical microscope—developed the first prototype of the electron microscope. This development led to the development of the field of electron microscopy. In the transmission electron microscope (TEM), electrons are produced by a hot tungsten element and accelerated by a potential difference in an electron gun, which gives them up to 400...
5.3K

You might also read

Related Articles

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

Sort by
Same author

Multiplexed Crossbar GFET Array With BioADC for Multi-Modal Aptamer-Based Sensing.

IEEE transactions on biomedical circuits and systems·2026
Same author

Use of AI agents to assess preoperative frailty in cancer patients.

npj digital surgery·2026
Same author

Lifetime cumulative effect of reproductive factors, "Life's essential 8" health status and risk of chronic kidney disease: a nationwide prospective cohort study.

BMC public health·2026
Same author

ELN orchestrates prometastatic and immunosuppressive niche in bladder cancer via TGFB1 autocrine signaling.

JCI insight·2026
Same author

Cortical and Cortico-Muscular Network Modulation Pattern of Eccentric and Concentric Movements in Fatigue State.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same author

The effects of insurance coverage under Shanghai hospital global budget management.

BMC health services research·2026
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

GoP-based Quality Enhancement on Video Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: May 24, 2025

Picometer-Precision Atomic Position Tracking through Electron Microscopy
15:04

Picometer-Precision Atomic Position Tracking through Electron Microscopy

Published on: July 3, 2021

6.5K

Dynamic Atomic Column Detection in Transmission Electron Microscopy Videos via Ridge Estimation.

Yuchen Xu, Andrew M Thomas, Peter A Crozier

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |March 3, 2025
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces novel ridge detection algorithms for analyzing atomic-level object trajectories in Transmission Electron Microscopy (TEM) videos. The method effectively tracks objects over time, improving upon standard frame-by-frame analysis.

    More Related Videos

    Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis
    07:24

    Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis

    Published on: May 10, 2021

    5.5K
    Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
    10:23

    Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

    Published on: June 23, 2023

    2.3K

    Related Experiment Videos

    Last Updated: May 24, 2025

    Picometer-Precision Atomic Position Tracking through Electron Microscopy
    15:04

    Picometer-Precision Atomic Position Tracking through Electron Microscopy

    Published on: July 3, 2021

    6.5K
    Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis
    07:24

    Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis

    Published on: May 10, 2021

    5.5K
    Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
    10:23

    Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

    Published on: June 23, 2023

    2.3K

    Area of Science:

    • Material Science
    • Image Processing
    • Computational Physics

    Background:

    • Transmission Electron Microscopy (TEM) generates image sequences crucial for material analysis.
    • Current TEM video analysis often relies on frame-by-frame object recognition, limiting temporal insights.
    • Tracking atomic-level objects in TEM requires advanced methods to handle dynamic behavior.

    Purpose of the Study:

    • To develop advanced ridge detection algorithms for analyzing spatio-temporal image tensors from TEM videos.
    • To enable non-parametric estimation of atomic-level object trajectories as a continuous function of time.
    • To improve the analysis of TEM image sequences by harnessing temporal correlations across frames.

    Main Methods:

    • Utilized ridge detection as a classical image processing tool adapted for material science.
    • Developed new algorithms for non-parametric trajectory estimation of atomic-level objects.
    • Applied spatio-temporal tensor analysis to long image sequences from TEM videos.
    • Tailored methods to handle objects with stochastic disappearance and reappearance.

    Main Results:

    • Demonstrated high effectiveness of the proposed method in simulation scenarios.
    • Achieved notable performance improvements in TEM experiments compared to existing benchmarks.
    • Successfully estimated explicit trajectories of atomic-level object locations over time.
    • Showcased the ability to track objects exhibiting stochastic behavior.

    Conclusions:

    • The novel ridge detection approach significantly enhances the analysis of TEM image sequences.
    • This method provides a more comprehensive understanding of atomic-level object dynamics than traditional techniques.
    • The approach offers a powerful new tool for material science research using TEM data.