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

Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

453
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,...
453
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

465
Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
465

You might also read

Related Articles

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

Sort by
Same author

Entropy for Prediction of MACEs in Myocarditis: A Cardiac MRI-based Biomarker of Myocardial Tissue Heterogeneity.

Radiology·2026
Same author

Retinal lesion annotation on fundus imaging: an interobserver variability study.

Scientific reports·2026
Same author

Impact of formalin fixation on biventricular parameters in cardiac diffusion tensor imaging: A pilot study in a miniature swine model.

The international journal of cardiovascular imaging·2026
Same author

Automatic dental crown generation with spatial constraint modeling.

Journal of medical imaging (Bellingham, Wash.)·2026
Same author

Artificial-intelligence-based feature mapping of native oxygenation-sensitive cardiovascular magnetic resonance images for classifying cardiomyopathies.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance·2026
Same author

Cardiac Magnetic Resonance Before Ventricular Tachycardia Ablation and During Follow-Up.

Circulation·2026

Related Experiment Video

Updated: Mar 7, 2026

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
06:56

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Published on: January 7, 2021

2.9K

Robust universal nonrigid motion correction framework for first-pass cardiac MR perfusion imaging.

Mitchel Benovoy1,2, Matthew Jacobs1,3, Farida Cheriet2

  • 1National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.

Journal of Magnetic Resonance Imaging : JMRI
|February 17, 2017
PubMed
Summary

This study introduces an automatic nonrigid image registration framework to accurately compensate for motion in cardiac MRI perfusion imaging. The system enhances myocardial perfusion quantification by improving image consistency across various acquisition settings.

Keywords:
cardiac magnetic resonancecontrast enhancementmotion correctionmyocardial perfusionnonrigid image registrationquantitative perfusion

More Related Videos

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
11:13

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Published on: May 24, 2021

7.4K
Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
08:35

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction

Published on: August 17, 2022

3.3K

Related Experiment Videos

Last Updated: Mar 7, 2026

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
06:56

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Published on: January 7, 2021

2.9K
Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
11:13

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Published on: May 24, 2021

7.4K
Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
08:35

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction

Published on: August 17, 2022

3.3K

Area of Science:

  • Medical Imaging
  • Cardiovascular Imaging
  • Image Processing

Background:

  • Cardiac MRI perfusion imaging is crucial for myocardial assessment.
  • Motion artifacts significantly degrade image quality and hinder accurate quantification.
  • Existing methods often struggle with the wide range of conditions in clinical cardiac MRI.

Purpose of the Study:

  • To develop and validate an automatic nonrigid image registration framework for cardiac MRI.
  • To compensate for motion in perfusion series and auxiliary images.
  • To facilitate accurate myocardial perfusion quantification.

Main Methods:

  • A framework combining discrete feature matching and variational optical flow in a multithreaded architecture.
  • Evaluation on 291 clinical subjects across 1.5T and 3.0T scanners.
  • Registration of steady-state free-precession (FISP) and fast low-angle shot (FLASH) dynamic contrast myocardial perfusion images, arterial input function (AIF), and proton density (PD)-weighted images under breath-hold (BH) and free-breath (FB) settings.

Main Results:

  • Significantly improved frame-to-frame appearance consistency (R² = 0.996 ± 3.735E-3 vs. 0.978 ± 2.024E-2, P < 0.0001).
  • Effective registration across BH and FB paradigms, and FISP and FLASH sequences.
  • Preservation of myocardial perfusion contrast dynamics (R² = 0.995 ± 6.420E-3).

Conclusions:

  • The proposed framework offers a universal solution for motion correction in cardiac MRI.
  • It is applicable to diverse perfusion series and auxiliary images with varying acquisition parameters.
  • Enables critical motion correction for pixel-wise cardiac MR perfusion quantification.