Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system
Parallel Computing System (PCS) is currently used widely in many applications of complex problems involving high computations. This is because it has the capability to process computations efficiently using a parallel scheme. ARS cluster is a low-cost PCS developed to implement processing of full-fi...
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Online Access: | http://eprints.utm.my/id/eprint/26332/1/Segmentation%20of%20tumor%20in%20digital%20mammograms%20using%20wavelet%20transform%20modulus%20maxima%20on%20a%20low%20cost%20parallel%20computing%20system.pdf http://eprints.utm.my/id/eprint/26332/ https://link.springer.com/chapter/10.1007/978-3-642-21729-6_175 |
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my.utm.263322017-07-17T06:46:01Z http://eprints.utm.my/id/eprint/26332/ Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system Sulaiman, Hanifah Ibrahim, Arsmah Alias, Norma QA Mathematics Parallel Computing System (PCS) is currently used widely in many applications of complex problems involving high computations. This is because it has the capability to process computations efficiently using a parallel scheme. ARS cluster is a low-cost PCS developed to implement processing of full-field digital mammograms. In this system eight processors are used to communicate via the Ethernet network using LINUX which is Fedora 7 as the operating system and Matlab Distributed Computing Server (MDCS) as a platform to process the digital mammograms. In this paper the Wavelet Transforms Modulus Maxima (WTMM) method is used to detect the edge of tumor in digital mammogram implemented on the ARS cluster. The study involved 80 digitized mammographic images obtained from the Malaysian National Cancer Center (NCC). The performance of the PCS in detecting the edge of tumors in digital mammograms using WTMM on the ARS cluster is reported. The experimental results showed that the speedup of the PCS improves when the number of processors is increased. © 2011 Springer-Verlag. 2011 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/26332/1/Segmentation%20of%20tumor%20in%20digital%20mammograms%20using%20wavelet%20transform%20modulus%20maxima%20on%20a%20low%20cost%20parallel%20computing%20system.pdf Sulaiman, Hanifah and Ibrahim, Arsmah and Alias, Norma (2011) Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system. In: 5th Kuala Lumpur International Conference on Biomedical Engineering, BIOMED 2011, 20-23 June 2011, Conjunction with the 8th Asian Pacific Conference on Medical and Biological Engineering, APCMBE 2011;Kuala Lumpur. https://link.springer.com/chapter/10.1007/978-3-642-21729-6_175 |
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Parallel Computing System (PCS) is currently used widely in many applications of complex problems involving high computations. This is because it has the capability to process computations efficiently using a parallel scheme. ARS cluster is a low-cost PCS developed to implement processing of full-field digital mammograms. In this system eight processors are used to communicate via the Ethernet network using LINUX which is Fedora 7 as the operating system and Matlab Distributed Computing Server (MDCS) as a platform to process the digital mammograms. In this paper the Wavelet Transforms Modulus Maxima (WTMM) method is used to detect the edge of tumor in digital mammogram implemented on the ARS cluster. The study involved 80 digitized mammographic images obtained from the Malaysian National Cancer Center (NCC). The performance of the PCS in detecting the edge of tumors in digital mammograms using WTMM on the ARS cluster is reported. The experimental results showed that the speedup of the PCS improves when the number of processors is increased. © 2011 Springer-Verlag. |
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Conference or Workshop Item |
author |
Sulaiman, Hanifah Ibrahim, Arsmah Alias, Norma |
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Sulaiman, Hanifah Ibrahim, Arsmah Alias, Norma |
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Sulaiman, Hanifah |
title |
Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system |
title_short |
Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system |
title_full |
Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system |
title_fullStr |
Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system |
title_full_unstemmed |
Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system |
title_sort |
segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system |
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2011 |
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http://eprints.utm.my/id/eprint/26332/1/Segmentation%20of%20tumor%20in%20digital%20mammograms%20using%20wavelet%20transform%20modulus%20maxima%20on%20a%20low%20cost%20parallel%20computing%20system.pdf http://eprints.utm.my/id/eprint/26332/ https://link.springer.com/chapter/10.1007/978-3-642-21729-6_175 |
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