Brain matters emphasis in MRI by kernel independent component analysis

Tomoko Tateyama, Zensho Nakao, Yen Wei Chen

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

3 被引用数 (Scopus)

抄録

We propose a new method for brain matters emphasis in MR Images based on Kernel Independent Component Analysis (KICA). First the method mappes MRI data into a higher-dimensional implicit feature space. Then we extract kernel independent components from 3-dimensional MR images; PD image, T1 image and T2 image by KICA. Since the KICA algorithm is based on minimization of a contrast function, it can perform image processing, considering a higher-dimensional non-linear model. We also give experimental results which are very helpful to emphasize tissue clusters included in images; not only giving contrast emphasis of the images but also image comparisons by with those ICA analysis.

本文言語英語
ホスト出版物のタイトルProceedings - 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007.
ページ117-120
ページ数4
DOI
出版ステータス出版済み - 2007
外部発表はい
イベント3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007 - Kaohsiung, 台湾
継続期間: 26-11-200728-11-2007

出版物シリーズ

名前Proceedings - 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007.
1

会議

会議3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007
国/地域台湾
CityKaohsiung
Period26-11-0728-11-07

All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • 信号処理
  • 情報システムおよび情報管理

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