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Related Concept Videos

Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

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, evaluates...
Imaging Studies for Cardiovascular System II:Types of Echocardiography01:20

Imaging Studies for Cardiovascular System II:Types of Echocardiography

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 diagnosing...

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Related Experiment Video

Updated: Jul 17, 2026

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

A novel two-dimensional echocardiographic image analysis system using artificial intelligence-learned pattern

Maxime Cannesson1, Masaki Tanabe, Matthew S Suffoletto

  • 1Cardiovascular Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15213-2582, USA.

Journal of the American College of Cardiology
|January 16, 2007
PubMed
Summary

An AI-powered system, Auto EF, rapidly and accurately calculates ejection fraction (EF) from echocardiograms, offering a significant improvement over manual methods.

More Related Videos

Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
06:34

Evaluation of Left Ventricular Structure and Function using 3D Echocardiography

Published on: October 28, 2020

Related Experiment Videos

Last Updated: Jul 17, 2026

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

Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
06:34

Evaluation of Left Ventricular Structure and Function using 3D Echocardiography

Published on: October 28, 2020

Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Manual echocardiographic ejection fraction (EF) calculation is time-consuming and subjective.
  • Visual assessment of EF lacks reproducibility.

Purpose of the Study:

  • To evaluate a novel AI-driven system for rapid and reproducible EF calculation.
  • To compare AI-based EF measurements with established methods.

Main Methods:

  • A 2D echocardiographic analysis system (Auto EF) trained on >10,000 tracings was used.
  • Auto EF automatically tracked the left ventricle endocardium to calculate EF.
  • Results were compared against manual biplane Simpson's rule, visual EF, and MRI.

Main Results:

  • Auto EF was successful in 92% of patients, with 77% fully automated.
  • High correlation was found between Auto EF and manual EF (r=0.98), and MRI EF (r=0.95).
  • Auto EF demonstrated lower interobserver variability than visual EF and improved accuracy for novice readers.

Conclusions:

  • AI-based Auto EF provides rapid, reproducible, and accurate ejection fraction calculations.
  • The system shows potential for clinical application in echocardiography.
  • Auto EF offers advantages over subjective visual assessment and time-consuming manual tracing.