Automated, nonrigid alignment of clinical myocardial contrast echocardiography image sequences

comparison with manual alignment

J Alison Noble, Dana Dawson, Jonathan Lindner, Jiri Sklenar, Sanjiv Kaul

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Analysis of myocardial contrast echocardiography (MCE) images is currently done by manual techniques. The development of computationally efficient methods for aligning images provides an important first step toward the automation of MCE analysis. This is challenging because a nonrigid transformation correction is required. In this paper, we evaluate a state-of-the-art nonrigid alignment method on clinical MCE image sequences (n = 58) acquired on patients during rest and dipyridamole stress, using both B-mode intermittent ultraharmonic (IUH) imaging and real-time myocardial perfusion imaging (RTMPI). Using manual alignment as the reference, we show quantitatively that the automated method aligns images as well as a human observer. However, the new method is faster and more reliable than manual alignment and removes the need for an experienced physician to perform it. The automated technique can be used for quick poststudy off-line analysis and has the potential to be incorporated into an ultrasound machine.
Original languageEnglish
Pages (from-to)115-123
Number of pages9
JournalUltrasound in Medicine & Biology
Volume28
Issue number1
Publication statusPublished - Jan 2002

Fingerprint

echocardiography
Echocardiography
alignment
Myocardial Perfusion Imaging
physicians
Dipyridamole
Automation
automation
Physicians

Keywords

  • Automation
  • Coronary Artery Disease
  • Echocardiography
  • Humans

Cite this

Automated, nonrigid alignment of clinical myocardial contrast echocardiography image sequences : comparison with manual alignment. / Noble, J Alison; Dawson, Dana; Lindner, Jonathan; Sklenar, Jiri; Kaul, Sanjiv.

In: Ultrasound in Medicine & Biology, Vol. 28, No. 1, 01.2002, p. 115-123.

Research output: Contribution to journalArticle

@article{ffad98bf38434ed5922cbac20efeafab,
title = "Automated, nonrigid alignment of clinical myocardial contrast echocardiography image sequences: comparison with manual alignment",
abstract = "Analysis of myocardial contrast echocardiography (MCE) images is currently done by manual techniques. The development of computationally efficient methods for aligning images provides an important first step toward the automation of MCE analysis. This is challenging because a nonrigid transformation correction is required. In this paper, we evaluate a state-of-the-art nonrigid alignment method on clinical MCE image sequences (n = 58) acquired on patients during rest and dipyridamole stress, using both B-mode intermittent ultraharmonic (IUH) imaging and real-time myocardial perfusion imaging (RTMPI). Using manual alignment as the reference, we show quantitatively that the automated method aligns images as well as a human observer. However, the new method is faster and more reliable than manual alignment and removes the need for an experienced physician to perform it. The automated technique can be used for quick poststudy off-line analysis and has the potential to be incorporated into an ultrasound machine.",
keywords = "Automation, Coronary Artery Disease, Echocardiography, Humans",
author = "Noble, {J Alison} and Dana Dawson and Jonathan Lindner and Jiri Sklenar and Sanjiv Kaul",
year = "2002",
month = "1",
language = "English",
volume = "28",
pages = "115--123",
journal = "Ultrasound in Medicine & Biology",
issn = "0301-5629",
publisher = "Elsevier USA",
number = "1",

}

TY - JOUR

T1 - Automated, nonrigid alignment of clinical myocardial contrast echocardiography image sequences

T2 - comparison with manual alignment

AU - Noble, J Alison

AU - Dawson, Dana

AU - Lindner, Jonathan

AU - Sklenar, Jiri

AU - Kaul, Sanjiv

PY - 2002/1

Y1 - 2002/1

N2 - Analysis of myocardial contrast echocardiography (MCE) images is currently done by manual techniques. The development of computationally efficient methods for aligning images provides an important first step toward the automation of MCE analysis. This is challenging because a nonrigid transformation correction is required. In this paper, we evaluate a state-of-the-art nonrigid alignment method on clinical MCE image sequences (n = 58) acquired on patients during rest and dipyridamole stress, using both B-mode intermittent ultraharmonic (IUH) imaging and real-time myocardial perfusion imaging (RTMPI). Using manual alignment as the reference, we show quantitatively that the automated method aligns images as well as a human observer. However, the new method is faster and more reliable than manual alignment and removes the need for an experienced physician to perform it. The automated technique can be used for quick poststudy off-line analysis and has the potential to be incorporated into an ultrasound machine.

AB - Analysis of myocardial contrast echocardiography (MCE) images is currently done by manual techniques. The development of computationally efficient methods for aligning images provides an important first step toward the automation of MCE analysis. This is challenging because a nonrigid transformation correction is required. In this paper, we evaluate a state-of-the-art nonrigid alignment method on clinical MCE image sequences (n = 58) acquired on patients during rest and dipyridamole stress, using both B-mode intermittent ultraharmonic (IUH) imaging and real-time myocardial perfusion imaging (RTMPI). Using manual alignment as the reference, we show quantitatively that the automated method aligns images as well as a human observer. However, the new method is faster and more reliable than manual alignment and removes the need for an experienced physician to perform it. The automated technique can be used for quick poststudy off-line analysis and has the potential to be incorporated into an ultrasound machine.

KW - Automation

KW - Coronary Artery Disease

KW - Echocardiography

KW - Humans

M3 - Article

VL - 28

SP - 115

EP - 123

JO - Ultrasound in Medicine & Biology

JF - Ultrasound in Medicine & Biology

SN - 0301-5629

IS - 1

ER -