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Related Experiment Video

Updated: May 31, 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

Segmentation of 3D RF echocardiography using a multiframe spatio-temporal predictor.

Paul C Pearlman1, Hemant D Tagare, Ben A Lin

  • 1Department of Electrical Engineering, Yale University, New Haven, CT, USA. paul.pearlman@yale.edu

Information Processing in Medical Imaging : Proceedings of the ... Conference
|July 19, 2011
PubMed
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This study introduces a new method for segmenting left ventricular endocardial boundaries using radiofrequency (RF) ultrasound. The approach enhances accuracy and robustness by combining spatial and multiframe conditional models for improved cardiac imaging analysis.

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Ultrasound Technology

Background:

  • Segmentation of left ventricular endocardial boundaries is crucial for cardiac function assessment.
  • Traditional B-mode ultrasound segmentation faces challenges with image inhomogeneities.
  • Accurate boundary detection is essential for quantitative analysis of cardiac mechanics.

Purpose of the Study:

  • To develop and validate an improved method for segmenting left ventricular endocardial boundaries using RF ultrasound data.
  • To overcome limitations of B-mode segmentation by leveraging RF signal properties.
  • To enhance the robustness and accuracy of cardiac segmentation through a multiframe approach.

Main Methods:

  • Joint segmentation using an independent identically distributed (i.i.d.) spatial model for RF intensity.

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Last Updated: May 31, 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

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

  • A computationally efficient multiframe conditional model exploiting spatio-temporal coherence.
  • Utilizing 2 to 5 frames of RF data for each segmentation process.

    • Main Results:

    • The proposed RF ultrasound segmentation method overcomes image inhomogeneities common in B-mode.
    • The multiframe conditional model significantly improves segmentation robustness and accuracy.
    • Validation against manual tracings and automated B-mode level sets demonstrates competitive performance.

    Conclusions:

    • The presented RF ultrasound segmentation approach offers a robust and accurate method for left ventricular endocardial boundary detection.
    • This technique provides geometric constraints beneficial for RF phase-based speckle tracking.
    • The multiframe strategy enhances diagnostic capabilities in echocardiography.