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Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation

FCM does not use spatial information in clustering process. Therefore, it is not robust against noise and other imaging artefacts. In order to incorporate spatial information, an extension for FCM (FCM_S) is proposed which allows pixel to be labelled by influence of its neighbourhood labels. FCM_S i...

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主要な著者: Balafar, Mohammad Ali, Ramli, Abdul Rahman, Mashohor, Syamsiah, Farzan, Ali
フォーマット: Conference or Workshop Item
言語:English
出版事項: IEEE 2010
オンライン･アクセス:http://psasir.upm.edu.my/id/eprint/68752/1/Compare%20different%20spatial%20based%20fuzzy-C_mean%20%28FCM%29%20extensions%20for%20MRI%20image%20segmentation.pdf
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id oai:psasir.upm.edu.my:68752
record_format eprints
spelling oai:psasir.upm.edu.my:68752 http://psasir.upm.edu.my/id/eprint/68752/ Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation Balafar, Mohammad Ali Ramli, Abdul Rahman Mashohor, Syamsiah Farzan, Ali FCM does not use spatial information in clustering process. Therefore, it is not robust against noise and other imaging artefacts. In order to incorporate spatial information, an extension for FCM (FCM_S) is proposed which allows pixel to be labelled by influence of its neighbourhood labels. FCM_S is time-consuming. To over come this problem, FCM_S1 is introduced, which is faster. Then, FCM_EN and FGFCM are proposed which are faster than previous methods. Four spatial based extensions are simulated for FCM: FCM_S, FCM_S1, FCM_EN and FGFCM. In order to compare their quality, they are applied to simulated brain MRI images and similarity index is used to compare their quality quantitatively. IEEE 2010 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/68752/1/Compare%20different%20spatial%20based%20fuzzy-C_mean%20%28FCM%29%20extensions%20for%20MRI%20image%20segmentation.pdf Balafar, Mohammad Ali and Ramli, Abdul Rahman and Mashohor, Syamsiah and Farzan, Ali (2010) Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation. In: 2nd International Conference on Computer and Automation Engineering (ICCAE 2010), 26-28 Feb. 2010, Singapore. (pp. 609-611). 10.1109/ICCAE.2010.5451302
institution UPM IR
collection UPM IR
language English
description FCM does not use spatial information in clustering process. Therefore, it is not robust against noise and other imaging artefacts. In order to incorporate spatial information, an extension for FCM (FCM_S) is proposed which allows pixel to be labelled by influence of its neighbourhood labels. FCM_S is time-consuming. To over come this problem, FCM_S1 is introduced, which is faster. Then, FCM_EN and FGFCM are proposed which are faster than previous methods. Four spatial based extensions are simulated for FCM: FCM_S, FCM_S1, FCM_EN and FGFCM. In order to compare their quality, they are applied to simulated brain MRI images and similarity index is used to compare their quality quantitatively.
format Conference or Workshop Item
author Balafar, Mohammad Ali
Ramli, Abdul Rahman
Mashohor, Syamsiah
Farzan, Ali
spellingShingle Balafar, Mohammad Ali
Ramli, Abdul Rahman
Mashohor, Syamsiah
Farzan, Ali
Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation
author_facet Balafar, Mohammad Ali
Ramli, Abdul Rahman
Mashohor, Syamsiah
Farzan, Ali
author_sort Balafar, Mohammad Ali
title Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation
title_short Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation
title_full Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation
title_fullStr Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation
title_full_unstemmed Compare different spatial based fuzzy-C_mean (FCM) extensions for MRI image segmentation
title_sort compare different spatial based fuzzy-c_mean (fcm) extensions for mri image segmentation
publisher IEEE
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/68752/1/Compare%20different%20spatial%20based%20fuzzy-C_mean%20%28FCM%29%20extensions%20for%20MRI%20image%20segmentation.pdf
_version_ 1819298725179162624
score 13.4562235

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