Breast cancer diagnosis in digital mammogram using multiscale curvelet transform

This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised...

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Main Authors:	M.M., Eltoukhy, I., Faye, B.B., Samir
Format:	Article
Published:	2010
Subjects:	TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science
Online Access:	http://eprints.utp.edu.my/388/ http://eprints.utp.edu.my/388/1/10-BreastCancerDiag-Curv_1.pdf

id	utp-388
recordtype	eprints
spelling	utp-3882017-01-19T08:24:49Z Breast cancer diagnosis in digital mammogram using multiscale curvelet transform M.M., Eltoukhy I., Faye B.B., Samir TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59% classification accuracy rate, which indicate that curvelet transformation is a promising tool for analysis and classification of digital mammograms. Â© 2009 Elsevier Ltd. All rights reserved. 2010 Article NonPeerReviewed application/pdf http://eprints.utp.edu.my/388/1/10-BreastCancerDiag-Curv_1.pdf M.M., Eltoukhy and I., Faye and B.B., Samir (2010) Breast cancer diagnosis in digital mammogram using multiscale curvelet transform. Computerized Medical Imaging and Graphics . ISSN 8956111 http://eprints.utp.edu.my/388/
institution	Universiti Teknologi Petronas Universiti Teknologi Petronas
repository_type	Digital Repository
institution_category	Local University
building	UTP Repository
collection	Online Access
topic	TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science M.M., Eltoukhy I., Faye B.B., Samir Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
description	This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59% classification accuracy rate, which indicate that curvelet transformation is a promising tool for analysis and classification of digital mammograms. Â© 2009 Elsevier Ltd. All rights reserved.
format	Article
author	M.M., Eltoukhy I., Faye B.B., Samir
author_facet	M.M., Eltoukhy I., Faye B.B., Samir
author_sort	M.M., Eltoukhy
title	Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title_short	Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title_full	Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title_fullStr	Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title_full_unstemmed	Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title_sort	breast cancer diagnosis in digital mammogram using multiscale curvelet transform
publishDate	2010
url	http://eprints.utp.edu.my/388/ http://eprints.utp.edu.my/388/1/10-BreastCancerDiag-Curv_1.pdf
first_indexed	2018-09-08T10:01:41Z
last_indexed	2018-09-08T10:01:41Z
_version_	1611033111380885504

Breast cancer diagnosis in digital mammogram using multiscale curvelet transform

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