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

10.1K
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...
10.1K
Applications of EMF Measurements01:26

Applications of EMF Measurements

27
Electromotive force (EMF) measurements have a broad range of applications in various fields, including chemistry and physics. The electrochemical series, an arrangement of elements in order of their standard electrode potentials, can be determined through EMF measurements. Elements with lower standard potentials can reduce ions of elements with higher standard potentials.The standard cell potential, E°, allows for the calculation of the standard reaction Gibbs energy, ΔG°, and...
27

You might also read

Related Articles

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

Sort by
Same author

Hazards associated with superconducting magnet quench events: system requirements, application and consequences.

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

B1+rms for Implants: A Review of Intended Use.

Journal of magnetic resonance imaging : JMRI·2026
Same author

Electromagnetic and Electrophysiological Modeling of Cardiac Stimulation Thresholds in 13 MRI Gradient Systems and 56 Body Models.

Magnetic resonance in medicine·2026
Same author

Lenz effect in conductive nonmagnetic objects moved in MRI environments.

Magnetic resonance imaging·2026
Same author

MRI and Implant Safety at Low-Field and Ultralow-Field Strengths.

Journal of magnetic resonance imaging : JMRI·2025
Same author

Impact of Lower Limb Amputation on Implant Heating During 1.5 T MRI: Assessment of Active and Passive Device.

Magnetic resonance in medicine·2025
Same journal

Correction to "On the shape of the radiation survival curve in tumor spheroids: The role of oxygen heterogeneity".

Medical physics·2026
Same journal

Multi-view constrained semi-supervised vertebra detection for 3D ultrasound spine volume.

Medical physics·2026
Same journal

Accuracy of quantitative <sup>177</sup>Lu SPECT/CT imaging: A systematic review.

Medical physics·2026
Same journal

Physics-constrained dual-domain network for CBCT reconstruction from orthogonal X-rays in gynecologic radiotherapy.

Medical physics·2026
Same journal

Decomposition-based harmonization for quantitative PET imaging across scanners and radiotracers.

Medical physics·2026
Same journal

Development and evaluation of an in vivo dose-based monitoring system for electron FLASH radiation therapy.

Medical physics·2026
See all related articles

Related Experiment Video

Updated: Mar 8, 2026

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

354

Electromagnetic computation and modeling in MRI.

Xin Chen1, Michael Steckner1

  • 1Toshiba Medical Research Institute USA, Inc. 777 Beta Drive, Mayfield Village, OH, 44143, USA.

Medical Physics
|January 13, 2017
PubMed
Summary
This summary is machine-generated.

Electromagnetic (EM) modeling optimizes Magnetic Resonance Imaging (MRI) systems by refining magnetic fields. This approach addresses challenges in manufacturing, installation, and use for improved image quality and patient safety.

Keywords:
electromagnetic (EM) modelingmagnetic resonance imaging (MRI)

More Related Videos

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

3.7K
Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

9.4K

Related Experiment Videos

Last Updated: Mar 8, 2026

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

354
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

3.7K
Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

9.4K

Area of Science:

  • Medical Imaging
  • Applied Electromagnetics
  • Biophysics

Background:

  • Magnetic Resonance Imaging (MRI) relies on precise control of magnetic fields for image generation.
  • Manufacturing, installation, and operational use of MRI scanners present significant electromagnetic challenges.
  • Optimization of MRI systems requires advanced computational tools to manage complex magnetic field interactions.

Purpose of the Study:

  • To review the application of electromagnetic (EM) computational modeling in MRI system development.
  • To outline the challenges associated with optimizing main field, gradient, and radiofrequency (RF) magnetic fields in MRI.
  • To highlight how EM modeling aids in maintaining and improving MRI operational performance.

Main Methods:

  • Extensive use of electromagnetic (EM) computational modeling throughout the MRI lifecycle.
  • Analysis of magnetic field interactions, including main field, gradient fields, and RF fields.
  • Review of design trade-offs and optimization strategies for MRI components.

Main Results:

  • EM modeling is crucial for designing MRI magnets to exacting specifications.
  • Computational tools help overcome challenges in maintaining main field performance.
  • EM modeling addresses complexities in gradient and RF field optimization for imaging and safety.

Conclusions:

  • Electromagnetic computational modeling is indispensable for optimizing MRI system performance.
  • Effective EM modeling strategies are key to balancing imaging quality, patient safety, and cost.
  • Continued application of EM modeling will drive advancements in MRI technology.