Identification of myocardial infarction tissue based on texture analysis from ultrasound images

Texture is an important characteristic that can be used for identification and/or detection for surface defects or abnormalities. This research has developed an algorithm for identifying heart with suspected myocardial infarction problem based on texture analysis applied on echocardiography images....

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Main Author:	Nazori, Nazori
Format:	Thesis
Language:	English
Published:	2007
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/18683/1/NazoriPFKE2007.pdf
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id	my-utm-ep.18683
record_format	uketd_dc
spelling	my-utm-ep.186832018-08-30T08:03:58Z Identification of myocardial infarction tissue based on texture analysis from ultrasound images 2007-03 Nazori, Nazori TK Electrical engineering. Electronics Nuclear engineering Texture is an important characteristic that can be used for identification and/or detection for surface defects or abnormalities. This research has developed an algorithm for identifying heart with suspected myocardial infarction problem based on texture analysis applied on echocardiography images. A hybrid technique of wavelet extension transform with gray level co-occurrence matrix is proposed. In this work wavelet extension transform is used to form an image approximation with higher resolution. The gray level co-occurrence matrices computed for each subband are used to extract four feature vectors: entropy, contrast, energy (angular second moment) and homogeneity (inverse difference moment). The classifier used in this work is the Mahalanobis distance classifier. The method is tested with clinical data from echocardiography images of 30 patients. For each patient, tissue samples are taken from suspected infarcted area as well as from non infarcted (normal) area. For each patient, 10 image frames separated by some time interval are used and for each image frame 5 normal regions and 5 suspected myocardial infarction regions of 16x16 pixel size are analyzed. The proposed method has achieved 91.67% performance accuracy in classifying between normal and infarcted hearts. Thus, the proposed technique may be used as a computerized second opinion for determining whether a person is suffering from a myocardial infarction heart or not. 2007-03 Thesis http://eprints.utm.my/id/eprint/18683/ http://eprints.utm.my/id/eprint/18683/1/NazoriPFKE2007.pdf application/pdf en public phd doctoral Universiti Teknologi Malaysia, Fakulti Kejuruteraan Mekanikal Fakulti Kejuruteraan Mekanikal
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Nazori, Nazori Identification of myocardial infarction tissue based on texture analysis from ultrasound images
description	Texture is an important characteristic that can be used for identification and/or detection for surface defects or abnormalities. This research has developed an algorithm for identifying heart with suspected myocardial infarction problem based on texture analysis applied on echocardiography images. A hybrid technique of wavelet extension transform with gray level co-occurrence matrix is proposed. In this work wavelet extension transform is used to form an image approximation with higher resolution. The gray level co-occurrence matrices computed for each subband are used to extract four feature vectors: entropy, contrast, energy (angular second moment) and homogeneity (inverse difference moment). The classifier used in this work is the Mahalanobis distance classifier. The method is tested with clinical data from echocardiography images of 30 patients. For each patient, tissue samples are taken from suspected infarcted area as well as from non infarcted (normal) area. For each patient, 10 image frames separated by some time interval are used and for each image frame 5 normal regions and 5 suspected myocardial infarction regions of 16x16 pixel size are analyzed. The proposed method has achieved 91.67% performance accuracy in classifying between normal and infarcted hearts. Thus, the proposed technique may be used as a computerized second opinion for determining whether a person is suffering from a myocardial infarction heart or not.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Nazori, Nazori
author_facet	Nazori, Nazori
author_sort	Nazori, Nazori
title	Identification of myocardial infarction tissue based on texture analysis from ultrasound images
title_short	Identification of myocardial infarction tissue based on texture analysis from ultrasound images
title_full	Identification of myocardial infarction tissue based on texture analysis from ultrasound images
title_fullStr	Identification of myocardial infarction tissue based on texture analysis from ultrasound images
title_full_unstemmed	Identification of myocardial infarction tissue based on texture analysis from ultrasound images
title_sort	identification of myocardial infarction tissue based on texture analysis from ultrasound images
granting_institution	Universiti Teknologi Malaysia, Fakulti Kejuruteraan Mekanikal
granting_department	Fakulti Kejuruteraan Mekanikal
publishDate	2007
url	http://eprints.utm.my/id/eprint/18683/1/NazoriPFKE2007.pdf
_version_	1747815333057527808

Identification of myocardial infarction tissue based on texture analysis from ultrasound images

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