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

5.4K
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...
5.4K
Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

70
Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
70

You might also read

Related Articles

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

Sort by
Same author

BART Streams: Real-Time Reconstruction Using a Modular Framework for Pipeline Processing.

Magnetic resonance in medicine·2026
Same author

Fast Real-Time Cardiac MRI: a Review of Current Techniques and Future Directions.

Investigative magnetic resonance imaging·2026
Same author

Fast and Robust Diffusion Posterior Sampling for MR Image Reconstruction Using the Preconditioned Unadjusted Langevin Algorithm.

Magnetic resonance in medicine·2026
Same author

Comparative Assessment of Diagnostic Accuracy and Puncture Duration of Two Endoscopic Ultrasound Biopsy Needles (22G Franseen versus 20G Antegrade Core Trap) in Patients with Solid Pancreatic Lesions.

Digestion·2026
Same author

FENCE: Flexible Electric Noise Reduction Endo-Shield for the Suppression of Electromagnetic Interference in Low-Field MRI.

NMR in biomedicine·2026
Same author

Phase-Pole-Free Images and Smooth Coil Sensitivity Maps by Regularized Nonlinear Inversion.

Magnetic resonance in medicine·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: Aug 4, 2025

Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI
05:37

Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

Published on: October 20, 2023

1.5K

Free-Breathing Liver Fat, R₂* and B₀ Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-Based

Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal

    IEEE Transactions on Medical Imaging
    |April 4, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a new MRI method for free-breathing liver scans. It accurately measures liver fat and R2* without breath-holding, improving non-invasive liver assessment.

    More Related Videos

    Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
    09:21

    Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

    Published on: February 18, 2015

    12.2K
    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
    09:30

    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

    Published on: December 18, 2016

    19.6K

    Related Experiment Videos

    Last Updated: Aug 4, 2025

    Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI
    05:37

    Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

    Published on: October 20, 2023

    1.5K
    Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
    09:21

    Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

    Published on: February 18, 2015

    12.2K
    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
    09:30

    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

    Published on: December 18, 2016

    19.6K

    Area of Science:

    • Medical Imaging
    • Magnetic Resonance Imaging (MRI)
    • Liver Disease Assessment

    Background:

    • Liver volumetric acquisition traditionally requires breath-holding, which can be challenging for patients.
    • Accurate quantification of liver fat fraction and R2* is crucial for diagnosing and monitoring liver conditions like hepatic steatosis.
    • Existing MRI techniques may be limited by motion artifacts during free-breathing scans.

    Purpose of the Study:

    • To develop and validate a novel, free-breathing MRI sequence for liver volumetric acquisition.
    • To enable simultaneous estimation of physical parameter maps (water, fat, R2*, B0 inhomogeneity) and coil sensitivity maps.
    • To provide accurate and robust liver fat and R2* quantification without the need for breath-holding.

    Main Methods:

    • A stack-of-radial multi-echo asymmetric-echo MRI sequence was developed.
    • Regularized model-based reconstruction using the Berkeley Advanced Reconstruction Toolbox (BART) was implemented.
    • Locally low rank and temporal total variation regularization were applied to physical parameter maps.
    • Self-gated k-space data was utilized for reconstruction.

    Main Results:

    • The technique was successfully tested on phantoms, healthy volunteers, and patients with obesity, diabetes, and hepatic steatosis.
    • Quantitative accuracy of fat fraction and R2* was confirmed against reference breath-hold Cartesian scans.
    • The multi-echo radial sampling demonstrated fast k-space coverage and motion robustness.
    • Motion-resolved reconstruction enabled free-breathing quantification in multiple motion states.

    Conclusions:

    • The proposed free-breathing radial MRI technique offers a convenient and non-invasive tool for liver assessment.
    • It overcomes the limitations of breath-holding requirements in liver MRI.
    • This method facilitates accurate liver fat and R2* quantification, aiding in the diagnosis and management of liver diseases.