Presentation 2005-03-18
Analysis of Self-Mapping Characteristics for 1-D SOM with Narrow Space : Application to Brain MR Images
Sakura KADOWAKI, Kazuhito SATO, Masaki ISHII, Hirokazu MADOKORO, Atushi INUGAMI,
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Abstract(in English) In this paper, we analyzed self-mapping characteristics of 1-D SOM for MR brain images. We extracted slice images of interest and used them to classify the three tissues (cerebrospinal fluid (CSF), gray matter, and white matter) necessary in the diagnosis of brain atrophy. We derived convergence test standards in an evaluation experiment by visualizing the weight vectors of SOM, and observing state transitions during the learning processes. From the correlation coefficient of the weight vectors, we divided the mapping results into two partial problems, confirming that it is possible to optimize the mapping space for problems where the number of clusters is unknown and to label the extracted target.
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Keyword(in English) MRI / SOM / Segmentation / CAD
Paper # TL2004-66,PRMU2004-234
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Committee TL
Conference Date 2005/3/11(1days)
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Registration To Thought and Language (TL)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Analysis of Self-Mapping Characteristics for 1-D SOM with Narrow Space : Application to Brain MR Images
Sub Title (in English)
Keyword(1) MRI
Keyword(2) SOM
Keyword(3) Segmentation
Keyword(4) CAD
1st Author's Name Sakura KADOWAKI
1st Author's Affiliation Akita Industry Promotion Foundation()
2nd Author's Name Kazuhito SATO
2nd Author's Affiliation Akita Prefecture Industrial Technology Center
3rd Author's Name Masaki ISHII
3rd Author's Affiliation Akita Prefecture Industrial Technology Center
4th Author's Name Hirokazu MADOKORO
4th Author's Affiliation Akita Prefecture Industrial Technology Center
5th Author's Name Atushi INUGAMI
5th Author's Affiliation Akita Kumiai General Hospital
Date 2005-03-18
Paper # TL2004-66,PRMU2004-234
Volume (vol) vol.104
Number (no) 740
Page pp.pp.-
#Pages 6
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