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

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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...
Magnetic Field Of A Current Loop01:16

Magnetic Field Of A Current Loop

Consider a circular loop with a radius a, that carries a current I. The magnetic field due to the current at an arbitrary point P along the axis of the loop can be calculated using the Biot-Savart law.
Plane Electromagnetic Waves II01:29

Plane Electromagnetic Waves II

Consider a plane wavefront traveling in position x-direction with a constant speed. This wavefront can be utilized to obtain the relationship between electric and magnetic fields with the help of Faraday's law.
Magnetic Field Lines01:19

Magnetic Field Lines

The representation of magnetic fields by magnetic field lines is very useful in visualizing the strength and direction of the magnetic field. Each of the magnetic field lines forms a closed loop. The field lines emerge from the north pole (N), loop around to the south pole (S), and continue through the bar magnet back to the north pole.
Magnetic field lines follow several hard-and-fast rules:

You might also read

Related Articles

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

Sort by
Same author

Hyperpolarization of [1-<sup>13</sup>C]Ketoisocaproate-d<sub>2</sub> by Reversible Exchange with Parahydrogen Enables Profiling of Branched-Chain-Amino-Acid Metabolism in Cellulo and in Vivo.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

A vendor-neutral functional MRI acquisition protocol for multi-site studies.

Aperture neuro·2026
Same author

Concomitant Gradient Effects Across Field Strengths and Gradient Amplitudes: Improved Estimation of Errors and Correction of Concomitant Dephasing and Diffusion Weighting.

Magnetic resonance in medicine·2026
Same author

OpenMRF: A Modular, Vendor-Neutral Open-Source Framework for Reproducible Magnetic Resonance Fingerprinting using Pulseq.

ArXiv·2026
Same author

Clinical Evaluation of Scout Accelerated Motion Estimation and Reduction (SAMER) Motion-Corrected 2D T2-Weighted TSE 3T Brain MRI in the Neurologic Intensive Care Unit.

AJNR. American journal of neuroradiology·2026
Same author

Correction: Naming convention for gradient system transfer function and gradient system frequency response for magnetic resonance imaging encoding field characterization.

Magma (New York, N.Y.)·2026
Same journal

LLM-enhanced Neuron Segmentation and Reconstruction in Complex Mouse Brain Images.

IEEE transactions on medical imaging·2026
Same journal

Matrixed-Spectrum Decomposition Accelerated Linear Boltzmann Transport Equation Solver for Fast Scatter Correction in Multi-Spectral CT.

IEEE transactions on medical imaging·2026
Same journal

The Ritz Adjoint Method for MRI Pulse Design.

IEEE transactions on medical imaging·2026
Same journal

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

IEEE transactions on medical imaging·2026
Same journal

Informed-Exploration Reinforcement Learning for Automated Virtual Coronary Intervention Planning.

IEEE transactions on medical imaging·2026
Same journal

4D Reconstruction of Fetal Left Ventricle from Echocardiography via 2.5D Radial Segmentation and Graph-Fourier Reconstruction.

IEEE transactions on medical imaging·2026
See all related articles

Related Experiment Video

Updated: Jun 13, 2026

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples
07:01

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

Direct magnetic field estimation based on echo planar raw data.

Frederik Testud1, Daniel Nicolas Splitthoff, Oliver Speck

  • 1Department of Radiology, Medical Physics, University Hospital Freiburg, D-79106 Freiburg, Germany. frederik.testud@uniklinik-freiburg.de

IEEE Transactions on Medical Imaging
|May 6, 2010
PubMed
Summary
This summary is machine-generated.

This study compares methods for correcting magnetic field inhomogeneities in functional magnetic resonance imaging. The k-space filtering analysis proved most effective at detecting these field variations.

More Related Videos

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement
09:43

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement

Published on: November 7, 2017

Related Experiment Videos

Last Updated: Jun 13, 2026

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples
07:01

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement
09:43

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement

Published on: November 7, 2017

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Neuroimaging
  • Biophysics

Background:

  • Gradient recalled echo echo planar imaging is crucial for functional MRI.
  • Field inhomogeneities cause artifacts, compromising image quality.
  • Current correction methods assume static field distributions, which is often inaccurate.

Purpose of the Study:

  • To compare and extend methods for extracting magnetic field distributions from k-space data or phase images.
  • To provide a theoretical basis for comparing k-space and image-phase approaches.
  • To introduce improvements to echo shift analysis, termed 'k-space filtering analysis'.

Main Methods:

  • Extraction of magnetic field distribution from k-space data.
  • Extraction of magnetic field distribution from reconstructed phase images.
  • Comparison of k-space and image-phase based approaches.
  • Extension of image phase analysis to calculate local gradients.
  • Improvements to echo shift analysis (k-space filtering analysis).

Main Results:

  • Demonstrated equivalence between k-space and image-phase based approaches.
  • Extended image phase analysis for gradient calculation.
  • Introduced and validated the 'k-space filtering analysis'.
  • Experimental comparison with phantom and in vivo B(0) maps.

Conclusions:

  • The k-space filtering analysis is the most sensitive method for detecting field inhomogeneities.
  • The developed methods offer a robust theoretical framework for artifact correction in fMRI.
  • Accurate B(0) mapping is essential for high-quality functional MRI data.