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Related Experiment Video

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Semi-automated Optical Heartbeat Analysis of Small Hearts
12:10

Semi-automated Optical Heartbeat Analysis of Small Hearts

Published on: September 16, 2009

A method for the dynamic analysis of the heart using a Lyapounov based denoising algorithm.

Jacinto C Nascimento1, João M Sanches, Jorge S Marques

  • 1Inst. de Sistemas e Robótica, Inst. Superior Técnico.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
Summary

This study introduces a new algorithm for accurate heart tracking in ultrasound images, overcoming noise and low contrast challenges for reliable left ventricle estimation during the cardiac cycle.

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Last Updated: Jul 10, 2026

Semi-automated Optical Heartbeat Analysis of Small Hearts
12:10

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Published on: September 16, 2009

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
11:04

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

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

Published on: May 24, 2021

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Cardiovascular Ultrasound

Background:

  • Heart tracking in ultrasound is challenging due to speckle noise, low signal-to-noise ratio (SNR), and poor contrast.
  • Feature detection methods often yield numerous outliers, hindering robust estimation of cardiac cavities.

Purpose of the Study:

  • To develop an efficient and accurate algorithm for heart tracking in ultrasound sequences.
  • To improve the estimation of cardiac structures, specifically the left ventricle, throughout the cardiac cycle.

Main Methods:

  • A novel denoising algorithm utilizing the Lyapounov equation.
  • Integration with a robust feature tracking algorithm designed to handle outlier features.

Main Results:

  • The proposed algorithm demonstrates computational efficiency.
  • Accurate estimates of the left ventricle were achieved during the cardiac cycle.

Conclusions:

  • The combined denoising and robust tracking approach effectively addresses challenges in ultrasound heart tracking.
  • The algorithm provides a computationally efficient and accurate solution for left ventricle estimation.