Presentation 2005-05-19
Principle Component Analysis for Region-based Segmentation of MR Images
Yuta IWASAKI, Yen Wei CHEN,
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Abstract(in English) In this paper, we proposed a robust segmentation method for MR images with noise by using region information. The feature vector is extracted from a 3x3 region. Compared with the conventional pixel-based method, the proposed region-based method is tolerant and robust to the noise, but the dimensionality of the feature vector is much larger than that of the conventional method. We also propose to use principle component analysis (PCA) as a preprocessing to reduce the large dimensionality. The experimental results show that the proposed method is superior to the conventional method with the same dimensionality of feature vector. In addition, the algorithm of K-means is used for un-supervised clustering.
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Keyword(in English) Principle Component Analysis / MR image / robust segmentation / un-supervised clustering
Paper # PRMU2005-10,MI2005-10
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Conference Information
Committee PRMU
Conference Date 2005/5/12(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Principle Component Analysis for Region-based Segmentation of MR Images
Sub Title (in English)
Keyword(1) Principle Component Analysis
Keyword(2) MR image
Keyword(3) robust segmentation
Keyword(4) un-supervised clustering
1st Author's Name Yuta IWASAKI
1st Author's Affiliation Information Science and Systems Engineering, Graduate School of Science and Engineering, Ritsumeikan University()
2nd Author's Name Yen Wei CHEN
2nd Author's Affiliation Department of Media Technology, Callege of Information Science and Engineering, Ritsumeikan University
Date 2005-05-19
Paper # PRMU2005-10,MI2005-10
Volume (vol) vol.105
Number (no) 62
Page pp.pp.-
#Pages 6
Date of Issue