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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| Format: | Article |
| Language: | English |
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2010
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| Online Access: | http://scholars.utp.edu.my/id/eprint/388/ http://scholars.utp.edu.my/id/eprint/388/1/10-BreastCancerDiag-Curv_1.pdf |
| _version_ | 1848658974218387456 |
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| author | M.M., Eltoukhy I., Faye B.B., Samir |
| author_facet | M.M., Eltoukhy I., Faye B.B., Samir |
| author_sort | M.M., Eltoukhy |
| 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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| first_indexed | 2025-11-13T07:23:03Z |
| format | Article |
| id | oai:scholars.utp.edu.my:388 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:23:03Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:3882017-01-19T08:24:49Z http://scholars.utp.edu.my/id/eprint/388/ 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. © 2009 Elsevier Ltd. All rights reserved. 2010 Article NonPeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/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 |
| 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 |
| title | Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
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| title_full | Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
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| title_fullStr | Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
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| title_full_unstemmed | Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
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| title_short | Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
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| title_sort | breast cancer diagnosis in digital mammogram using multiscale curvelet transform |
| topic | TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/388/ http://scholars.utp.edu.my/id/eprint/388/1/10-BreastCancerDiag-Curv_1.pdf |