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

2.4K
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...
2.4K
Computed Tomography01:10

Computed Tomography

4.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
4.6K
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

5.2K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
5.2K
Magnetic Vector Potential01:15

Magnetic Vector Potential

697
In electrostatics, the electric field can be written as the negative gradient of the potential. In magnetostatics, the zero divergence of the magnetic field ensures that the magnetic field can be expressed as the curl of a vector potential. This potential is known as the magnetic vector potential.
Consider an ideal solenoid with n turns per unit length and radius R. If I is the current through the solenoid, the magnetic field inside the solenoid is expressed as the product of vacuum...
697

You might also read

Related Articles

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

Sort by
Same author

Computed Tomography-Based Assessment of Sarcopenia and Disease Progression in Pancreatic Ductal Adenocarcinoma: A Radiomics and Machine Learning Approach.

Gastroenterology research·2026
Same author

The reactivity of single magnesium nanoparticles towards corrosion and galvanic replacement.

Nanoscale·2026
Same author

Quantum Confinement Effect in a Heteromorphic PbS/SnS<sub>2</sub> Superlattice Grown by Atomic Layer Deposition.

ACS nano·2026
Same author

Octadecene-free colloidal synthesis of CsPbI<sub>3</sub> nanocrystals with improved size, shape and phase control.

Nanoscale·2026
Same author

Structural properties, polymorphism, and multiscale disorder unravel energy transport limitations in perylene diimide semiconductors.

Science advances·2026
Same author

Magnesium film-over-nanospheres (FONs) for surface-enhanced Raman scattering.

Faraday discussions·2026
Same journal

Predictive drift compensation of multi-frame STEM via live scan modification.

Ultramicroscopy·2026
Same journal

Deep PACBED: Multitask analysis of PACBED images using deep neural networks.

Ultramicroscopy·2026
Same journal

Guided progressive reconstructive imaging: A new quantization-based framework for low-dose, high-throughput and real-time analytical ptychography.

Ultramicroscopy·2026
Same journal

Brightness optimization in a 200 keV DTEM source by geometry-driven aberration suppression.

Ultramicroscopy·2026
Same journal

Characterization of the Timepix4 hybrid pixel detector and its impact on four-dimensional scanning transmission electron microscopy (4D-STEM).

Ultramicroscopy·2026
Same journal

Contamination analysis of the residual gas composition in transmission electron microscopy.

Ultramicroscopy·2026
See all related articles

Related Experiment Video

Updated: Jul 22, 2025

Array Tomography Workflow for the Targeted Acquisition of Volume Information using Scanning Electron Microscopy
09:47

Array Tomography Workflow for the Targeted Acquisition of Volume Information using Scanning Electron Microscopy

Published on: July 15, 2021

4.9K

WRAP: A wavelet-regularised reconstruction algorithm for magnetic vector electron tomography.

George R Lewis1, Daniel Wolf2, Axel Lubk3

  • 1Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK; Department of Earth Sciences, University of Cambridge, Cambridge, CB2 3EQ, UK.

Ultramicroscopy
|July 23, 2023
PubMed
Summary
This summary is machine-generated.

A new algorithm, WRAP (Wavelet Regularised A Program), significantly improves 3D magnetic field reconstruction in magnetic vector electron tomography (VET). This technique enhances understanding of nanoscale magnetism, even with limited data.

Keywords:
Compressed sensingElectron microscopyInverse reconstructionNanomagnetismTomography

More Related Videos

Imaging Replicative Domains in Ultrastructurally Preserved Chromatin by Electron Tomography
14:56

Imaging Replicative Domains in Ultrastructurally Preserved Chromatin by Electron Tomography

Published on: May 20, 2022

3.8K
Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth
12:18

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth

Published on: February 9, 2012

12.5K

Related Experiment Videos

Last Updated: Jul 22, 2025

Array Tomography Workflow for the Targeted Acquisition of Volume Information using Scanning Electron Microscopy
09:47

Array Tomography Workflow for the Targeted Acquisition of Volume Information using Scanning Electron Microscopy

Published on: July 15, 2021

4.9K
Imaging Replicative Domains in Ultrastructurally Preserved Chromatin by Electron Tomography
14:56

Imaging Replicative Domains in Ultrastructurally Preserved Chromatin by Electron Tomography

Published on: May 20, 2022

3.8K
Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth
12:18

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth

Published on: February 9, 2012

12.5K

Area of Science:

  • Materials Science
  • Physics
  • Data Science

Background:

  • Magnetic vector electron tomography (VET) is crucial for understanding nanoscale magnetic phenomena.
  • High-resolution 3D magnetic field reconstruction is essential for VET.
  • Existing algorithms face limitations, especially with noisy or sparse data.

Purpose of the Study:

  • Introduce WRAP (Wavelet Regularised A Program), a novel reconstruction algorithm for magnetic VET.
  • Enhance the fidelity and robustness of 3D magnetic field reconstructions.
  • Validate WRAP's performance against conventional methods and experimental data.

Main Methods:

  • Developed WRAP, a compressed sensing algorithm utilizing wavelet domain sparsity.
  • Reconstructed the magnetic vector potential (A) directly.
  • Simulated noisy datasets and used experimental electron holography data for validation.

Main Results:

  • WRAP demonstrated a significant increase in 3D reconstruction fidelity.
  • Achieved approximately 60% improvement over conventional algorithms with limited, noisy data.
  • Successfully revealed detailed magnetism in CuCo nanowire vortex states using experimental data.

Conclusions:

  • WRAP represents a major advancement for magnetic VET.
  • The algorithm enhances the capability to probe magnetism at the nanoscale.
  • WRAP's robustness with limited data opens new possibilities for VET applications.