Cover Image

Determining features for discriminating PTB and normal lungs using phase congruency model

The appearance of the infected zone on the digital chest X-ray image for pulmonary tuberculosis (PTB) does not conform to standard shape, size or configuration. This study uses phase congruency (PC(x)) values to gather information from transition of adjacent pixel values that may be used as features...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohd. Rijal, Omar, Ebrahimian, Hossien, Mohd. Noor, Norliza
Format: Book Section
Published: IEEE 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/34713/
http://dx.doi.org/10.1109/BHI.2012.6211583
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.34713
record_format eprints
spelling my.utm.347132017-02-02T05:57:46Z http://eprints.utm.my/id/eprint/34713/ Determining features for discriminating PTB and normal lungs using phase congruency model Mohd. Rijal, Omar Ebrahimian, Hossien Mohd. Noor, Norliza TK Electrical engineering. Electronics Nuclear engineering The appearance of the infected zone on the digital chest X-ray image for pulmonary tuberculosis (PTB) does not conform to standard shape, size or configuration. This study uses phase congruency (PC(x)) values to gather information from transition of adjacent pixel values that may be used as features to represent known disease type. The feature vector consisting of the average, variance, coefficient of variation and maximum PC(x)-values was found to be able to detect PTB with high accuracy. IEEE 2012 Book Section PeerReviewed Mohd. Rijal, Omar and Ebrahimian, Hossien and Mohd. Noor, Norliza (2012) Determining features for discriminating PTB and normal lungs using phase congruency model. In: Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012. IEEE, New York, USA, pp. 341-344. ISBN 978-145772177-9 http://dx.doi.org/10.1109/BHI.2012.6211583 DOI:10.1109/BHI.2012.6211583
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd. Rijal, Omar
Ebrahimian, Hossien
Mohd. Noor, Norliza
Determining features for discriminating PTB and normal lungs using phase congruency model
description The appearance of the infected zone on the digital chest X-ray image for pulmonary tuberculosis (PTB) does not conform to standard shape, size or configuration. This study uses phase congruency (PC(x)) values to gather information from transition of adjacent pixel values that may be used as features to represent known disease type. The feature vector consisting of the average, variance, coefficient of variation and maximum PC(x)-values was found to be able to detect PTB with high accuracy.
format Book Section
author Mohd. Rijal, Omar
Ebrahimian, Hossien
Mohd. Noor, Norliza
author_facet Mohd. Rijal, Omar
Ebrahimian, Hossien
Mohd. Noor, Norliza
author_sort Mohd. Rijal, Omar
title Determining features for discriminating PTB and normal lungs using phase congruency model
title_short Determining features for discriminating PTB and normal lungs using phase congruency model
title_full Determining features for discriminating PTB and normal lungs using phase congruency model
title_fullStr Determining features for discriminating PTB and normal lungs using phase congruency model
title_full_unstemmed Determining features for discriminating PTB and normal lungs using phase congruency model
title_sort determining features for discriminating ptb and normal lungs using phase congruency model
publisher IEEE
publishDate 2012
url http://eprints.utm.my/id/eprint/34713/
http://dx.doi.org/10.1109/BHI.2012.6211583
_version_ 1643649653133017088
score 13.211869

Similar Items