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: Eltoukhy , M.M., Faye , Ibrahima, Brahim Belhaouari, Samir
Format: Article
Language:English
Published: Elsevier 2010
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/2724/
http://scholars.utp.edu.my/id/eprint/2724/1/paper.pdf
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author Eltoukhy , M.M.
Faye , Ibrahima
Brahim Belhaouari, Samir
author_facet Eltoukhy , M.M.
Faye , Ibrahima
Brahim Belhaouari, Samir
author_sort Eltoukhy , M.M.
building UTP Institutional Repository
collection Online Access
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. © 2009 Elsevier Ltd. All rights reserved.
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institution Universiti Teknologi Petronas
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language English
last_indexed 2025-11-13T07:28:08Z
publishDate 2010
publisher Elsevier
recordtype eprints
repository_type Digital Repository
spelling oai:scholars.utp.edu.my:27242017-01-19T08:24:41Z http://scholars.utp.edu.my/id/eprint/2724/ Breast cancer diagnosis in digital mammogram using multiscale curvelet transform Eltoukhy , M.M. Faye , Ibrahima Brahim Belhaouari, Samir TK Electrical engineering. Electronics Nuclear engineering 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. © 2009 Elsevier Ltd. All rights reserved. Elsevier 2010 Article PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/2724/1/paper.pdf Eltoukhy , M.M. and Faye , Ibrahima and Brahim Belhaouari, Samir (2010) Breast cancer diagnosis in digital mammogram using multiscale curvelet transform. Computerized Medical Imaging and Graphics, 34. pp. 269-276. ISSN 8956111 http://www.scopus.com/inward/record.url?eid=2-s2.0-71049184061&partnerID=40&md5=bdb54f98158d60893f6bae0e6847baa1 10.1016/j.compmedimag.2009.11.002 10.1016/j.compmedimag.2009.11.002 10.1016/j.compmedimag.2009.11.002
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Eltoukhy , M.M.
Faye , Ibrahima
Brahim Belhaouari, Samir
Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title 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_short Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
title_sort breast cancer diagnosis in digital mammogram using multiscale curvelet transform
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/2724/
http://scholars.utp.edu.my/id/eprint/2724/
http://scholars.utp.edu.my/id/eprint/2724/
http://scholars.utp.edu.my/id/eprint/2724/1/paper.pdf