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 I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

704
Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...
704
Imaging Studies for Cardiovascular System II:Types of Echocardiography01:20

Imaging Studies for Cardiovascular System II:Types of Echocardiography

609
Echocardiography plays a role in assessing cardiac health and detecting heart conditions, with various types providing critical insights for diagnosis and treatment.
Types of Echocardiography
Transthoracic Echocardiography (TTE)
TTE is the most common type of echocardiogram which involves placing a transducer on the patient's chest, emitting sound waves to create heart images. TTE is invaluable for evaluating the heart's size, structure, and motion, making it particularly useful for...
609

You might also read

Related Articles

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

Sort by
Same author

Anakinra for recurrent pericarditis: a retrospective evaluation of long-term effectiveness, initiation timing and tapering.

Rheumatology international·2026
Same author

Editorial: Responses to chronic stress in vertebrate animals: from molecules to behavior.

Frontiers in endocrinology·2026
Same author

Dynamic Trends of Secondary Tricuspid Regurgitation in Acute Heart Failure and Association With Outcomes.

The American journal of cardiology·2026
Same author

Combined pulsed field ablation and left atrial appendage occlusion in a patient with persistent atrial fibrillation and adenomyosis-related menorrhagia: case report and 1-year follow-up.

European heart journal. Case reports·2026
Same author

Artificial Intelligence for Prediction and Detection of Atrial Fibrillation from Sinus-Rhythm Electrocardiograms and Ambulatory Monitoring.

Biomedicines·2026
Same author

Sotatercept as an Add-On to Background Therapy in Idiopathic Pulmonary Arterial Hypertension: Insights from a Real-World Cohort.

Pharmaceuticals (Basel, Switzerland)·2026

Related Experiment Video

Updated: Jan 9, 2026

Transthoracic Speckle Tracking Echocardiography for the Quantitative Assessment of Left Ventricular Myocardial Deformation
09:05

Transthoracic Speckle Tracking Echocardiography for the Quantitative Assessment of Left Ventricular Myocardial Deformation

Published on: October 20, 2016

20.1K

Estimating Ejection Fraction from Single View Echocardiographic Images.

Eleftheria Vorgiazidou, Dimitris Filos, Athanasios Samaras

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    Summary

    This study presents an automated method for estimating ejection fraction (EF) using deep learning and echocardiography. The framework accurately quantifies EF, aiding in timely heart failure diagnosis and patient management.

    More Related Videos

    Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography
    07:11

    Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography

    Published on: October 28, 2020

    3.3K
    High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
    11:09

    High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

    Published on: December 16, 2022

    4.2K

    Related Experiment Videos

    Last Updated: Jan 9, 2026

    Transthoracic Speckle Tracking Echocardiography for the Quantitative Assessment of Left Ventricular Myocardial Deformation
    09:05

    Transthoracic Speckle Tracking Echocardiography for the Quantitative Assessment of Left Ventricular Myocardial Deformation

    Published on: October 20, 2016

    20.1K
    Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography
    07:11

    Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography

    Published on: October 28, 2020

    3.3K
    High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
    11:09

    High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

    Published on: December 16, 2022

    4.2K

    Area of Science:

    • Cardiovascular Imaging
    • Artificial Intelligence in Medicine
    • Echocardiography

    Background:

    • Heart failure (HF) is a major health concern, with ejection fraction (EF) crucial for diagnosis and management.
    • Accurate EF estimation is vital for guiding therapeutic decisions in cardiovascular imaging.

    Purpose of the Study:

    • To develop an automated framework for precise EF quantification using echocardiographic images.
    • To integrate deep learning and geometric modeling for enhanced left ventricle (LV) volume calculation.

    Main Methods:

    • Utilized a pair of four-chamber view (4CH) echocardiographic images (end-diastolic and end-systolic).
    • Employed an attention-based U-Net for LV segmentation.
    • Applied an ellipsoidal model for 3D LV reconstruction and EF calculation.

    Main Results:

    • Demonstrated minimal estimation errors compared to ground truth data.
    • Bland-Altman analysis confirmed strong agreement in EF measurements.
    • Achieved 82.0% accuracy in classifying EF groups, indicating clinical relevance.

    Conclusions:

    • The automated framework offers an affordable and accurate method for EF calculation.
    • This tool can support timely heart failure classification and management.
    • Further refinement of 3D ventricular volume reconstruction is needed for improved precision.