A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram.
This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram.Using multiresolution analysis,mammogram images are decomposed into different resolution levels,which are sensitive to different frequency bands. A set of the biggest coef...
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my.utp.eprints.27252017-01-19T08:24:41Z A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. Eltoukhy, M.M. Faye, Ibrahima Brahim Belhaouari, Samir QA75 Electronic computers. Computer science This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram.Using multiresolution analysis,mammogram images are decomposed into different resolution levels,which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2x5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant. Elsevier 2010 Citation Index Journal PeerReviewed application/pdf http://eprints.utp.edu.my/2725/1/eprints.pdf Eltoukhy, M.M. and Faye, Ibrahima and Brahim Belhaouari, Samir (2010) A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. [Citation Index Journal] http://eprints.utp.edu.my/2725/ |
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QA75 Electronic computers. Computer science Eltoukhy, M.M. Faye, Ibrahima Brahim Belhaouari, Samir A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
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This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram.Using multiresolution analysis,mammogram images are decomposed into different resolution levels,which are sensitive to different frequency bands. A set of the biggest
coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2x5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant. |
format |
Citation Index Journal |
author |
Eltoukhy, M.M. Faye, Ibrahima Brahim Belhaouari, Samir |
author_facet |
Eltoukhy, M.M. Faye, Ibrahima Brahim Belhaouari, Samir |
author_sort |
Eltoukhy, M.M. |
title |
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
title_short |
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
title_full |
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
title_fullStr |
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
title_full_unstemmed |
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
title_sort |
comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. |
publisher |
Elsevier |
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2010 |
url |
http://eprints.utp.edu.my/2725/1/eprints.pdf http://eprints.utp.edu.my/2725/ |
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1738655215672885248 |