Enhancement of myocardial boundary tracking using wavelet-based motion estimation

Adhi Harmoko Saputro, Mohd. Marzuki Mustafa, Aini Hussain, Oteh Maskon, Ika Faizura Mohd Nor

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Myocardial boundary tracking in echocardiograms is a challenging task due to soft tissue contrast, speckled noise, scattering and attenuation of the ultrasound signal. Furthermore, most ultrasound images that are acquired by physicians in clinical practice have a poor rating quality and are hard to analyze and recognize. Both of these factors could complicate the development of an algorithm to track the movement of myocardial boundary in echocardiograms. With this in mind, we proposed a method that combines a wavelet multi-scale strategy and a warping optical flow to generate a high-accuracy velocity vector from two consecutive frames of poor-quality ultrasound images. From these sets of high-accuracy velocity vectors, the movement of points along the myocardial boundary is tracked starting from the end diastole to the end systole of the cardiac cycle. A set of multi-scale images generated by Haar wavelet decomposition is processed recursively to compute the motion vector field in an echocardiographic image sequence. Artificially generated cardiac image sequences were used to measure performance by comparing the angular error of the proposed motion estimation technique to other established methods. The proposed method was also tested and evaluated by expert cardiologists using actual poor-quality ultrasound images that were acquired from healthy and unhealthy volunteers to track myocardial boundaries based on the parasternal long axis view of the human cardiac.

Original languageEnglish
Pages (from-to)1779-1792
Number of pages14
JournalJournal of Information and Computational Science
Volume8
Issue number10
Publication statusPublished - Oct 2011

Fingerprint

Motion estimation
Ultrasonics
estimation procedure
Wavelet decomposition
Optical flows
rating
physician
Acoustic noise
expert
Scattering
Tissue
performance

Keywords

  • Echocardiographic
  • Motion estimation
  • Myocardial boundary
  • Style guide
  • Wavelet decomposition

ASJC Scopus subject areas

  • Information Systems
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics
  • Library and Information Sciences

Cite this

Enhancement of myocardial boundary tracking using wavelet-based motion estimation. / Saputro, Adhi Harmoko; Mustafa, Mohd. Marzuki; Hussain, Aini; Maskon, Oteh; Nor, Ika Faizura Mohd.

In: Journal of Information and Computational Science, Vol. 8, No. 10, 10.2011, p. 1779-1792.

Research output: Contribution to journalArticle

@article{0c369cb5c059434688f318357c03b554,
title = "Enhancement of myocardial boundary tracking using wavelet-based motion estimation",
abstract = "Myocardial boundary tracking in echocardiograms is a challenging task due to soft tissue contrast, speckled noise, scattering and attenuation of the ultrasound signal. Furthermore, most ultrasound images that are acquired by physicians in clinical practice have a poor rating quality and are hard to analyze and recognize. Both of these factors could complicate the development of an algorithm to track the movement of myocardial boundary in echocardiograms. With this in mind, we proposed a method that combines a wavelet multi-scale strategy and a warping optical flow to generate a high-accuracy velocity vector from two consecutive frames of poor-quality ultrasound images. From these sets of high-accuracy velocity vectors, the movement of points along the myocardial boundary is tracked starting from the end diastole to the end systole of the cardiac cycle. A set of multi-scale images generated by Haar wavelet decomposition is processed recursively to compute the motion vector field in an echocardiographic image sequence. Artificially generated cardiac image sequences were used to measure performance by comparing the angular error of the proposed motion estimation technique to other established methods. The proposed method was also tested and evaluated by expert cardiologists using actual poor-quality ultrasound images that were acquired from healthy and unhealthy volunteers to track myocardial boundaries based on the parasternal long axis view of the human cardiac.",
keywords = "Echocardiographic, Motion estimation, Myocardial boundary, Style guide, Wavelet decomposition",
author = "Saputro, {Adhi Harmoko} and Mustafa, {Mohd. Marzuki} and Aini Hussain and Oteh Maskon and Nor, {Ika Faizura Mohd}",
year = "2011",
month = "10",
language = "English",
volume = "8",
pages = "1779--1792",
journal = "Journal of Information and Computational Science",
issn = "1548-7741",
publisher = "Binary Information Press",
number = "10",

}

TY - JOUR

T1 - Enhancement of myocardial boundary tracking using wavelet-based motion estimation

AU - Saputro, Adhi Harmoko

AU - Mustafa, Mohd. Marzuki

AU - Hussain, Aini

AU - Maskon, Oteh

AU - Nor, Ika Faizura Mohd

PY - 2011/10

Y1 - 2011/10

N2 - Myocardial boundary tracking in echocardiograms is a challenging task due to soft tissue contrast, speckled noise, scattering and attenuation of the ultrasound signal. Furthermore, most ultrasound images that are acquired by physicians in clinical practice have a poor rating quality and are hard to analyze and recognize. Both of these factors could complicate the development of an algorithm to track the movement of myocardial boundary in echocardiograms. With this in mind, we proposed a method that combines a wavelet multi-scale strategy and a warping optical flow to generate a high-accuracy velocity vector from two consecutive frames of poor-quality ultrasound images. From these sets of high-accuracy velocity vectors, the movement of points along the myocardial boundary is tracked starting from the end diastole to the end systole of the cardiac cycle. A set of multi-scale images generated by Haar wavelet decomposition is processed recursively to compute the motion vector field in an echocardiographic image sequence. Artificially generated cardiac image sequences were used to measure performance by comparing the angular error of the proposed motion estimation technique to other established methods. The proposed method was also tested and evaluated by expert cardiologists using actual poor-quality ultrasound images that were acquired from healthy and unhealthy volunteers to track myocardial boundaries based on the parasternal long axis view of the human cardiac.

AB - Myocardial boundary tracking in echocardiograms is a challenging task due to soft tissue contrast, speckled noise, scattering and attenuation of the ultrasound signal. Furthermore, most ultrasound images that are acquired by physicians in clinical practice have a poor rating quality and are hard to analyze and recognize. Both of these factors could complicate the development of an algorithm to track the movement of myocardial boundary in echocardiograms. With this in mind, we proposed a method that combines a wavelet multi-scale strategy and a warping optical flow to generate a high-accuracy velocity vector from two consecutive frames of poor-quality ultrasound images. From these sets of high-accuracy velocity vectors, the movement of points along the myocardial boundary is tracked starting from the end diastole to the end systole of the cardiac cycle. A set of multi-scale images generated by Haar wavelet decomposition is processed recursively to compute the motion vector field in an echocardiographic image sequence. Artificially generated cardiac image sequences were used to measure performance by comparing the angular error of the proposed motion estimation technique to other established methods. The proposed method was also tested and evaluated by expert cardiologists using actual poor-quality ultrasound images that were acquired from healthy and unhealthy volunteers to track myocardial boundaries based on the parasternal long axis view of the human cardiac.

KW - Echocardiographic

KW - Motion estimation

KW - Myocardial boundary

KW - Style guide

KW - Wavelet decomposition

UR - http://www.scopus.com/inward/record.url?scp=80355140638&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80355140638&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:80355140638

VL - 8

SP - 1779

EP - 1792

JO - Journal of Information and Computational Science

JF - Journal of Information and Computational Science

SN - 1548-7741

IS - 10

ER -