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A Support Construction for CT Image Based on K-Means Clustering
http://hdl.handle.net/10258/00009581
http://hdl.handle.net/10258/0000958168560073-a5fc-4dc5-a44d-b2cf223e72c6
名前 / ファイル | ライセンス | アクション |
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JCC_5_1_137_151 (5.7 MB)
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Item type | 学術雑誌論文 / Journal Article.(1) | |||||||||||
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公開日 | 2018-03-08 | |||||||||||
タイトル | ||||||||||||
言語 | en | |||||||||||
タイトル | A Support Construction for CT Image Based on K-Means Clustering | |||||||||||
言語 | ||||||||||||
言語 | eng | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | Sparse CT Reconstruction | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | K-Means Clustering | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | Total Variation Filtering | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | Maximum Entropy Thresholding | |||||||||||
資源タイプ | ||||||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
資源タイプ | journal article | |||||||||||
アクセス権 | ||||||||||||
アクセス権 | open access | |||||||||||
アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||||||
著者 |
DHAMMATORN, Wisan
× DHAMMATORN, Wisan× 塩谷, 浩之
WEKO
55044
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室蘭工業大学研究者データベースへのリンク | ||||||||||||
塩谷 浩之(SHIOYA Hiroyuki) | ||||||||||||
http://rdsoran.muroran-it.ac.jp/html/100000237_ja.html | ||||||||||||
抄録 | ||||||||||||
内容記述タイプ | Abstract | |||||||||||
内容記述 | Computer Tomography in medical imaging provides human internal body pictures in the digital form. The more quality images it provides, the better information we get. Normally, medical imaging can be constructed by projection data from several perspectives. In this paper, our research challenges and describes a numerical method for refining the image of a Region of Interest (ROI) by constructing support within a standard CT image. It is obvious that the quality of tomographic slice is affected by artifacts. CT using filter and K-means clustering provides a way to reconstruct an ROI with minimal artifacts and improve the degree of the spatial resolution. Experimental results are presented for improving the reconstructed images, showing that the approach enhances the overall resolution and contrast of ROI images. Our method provides a number of advantages: robustness with noise in projection data and support construction without the need to acquire any additional setup. | |||||||||||
言語 | en | |||||||||||
書誌情報 |
en : Journal of Computer and Communications 巻 05, 号 01, p. 137-151, 発行日 2017-01 |
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出版者 | ||||||||||||
言語 | en | |||||||||||
出版者 | Scientific Research Publishing | |||||||||||
出版者版へのリンク | ||||||||||||
10.4236/jcc.2017.51011 | ||||||||||||
https://doi.org/10.4236/jcc.2017.51011 | ||||||||||||
DOI | ||||||||||||
関連タイプ | isIdenticalTo | |||||||||||
識別子タイプ | DOI | |||||||||||
関連識別子 | 10.4236/jcc.2017.51011 | |||||||||||
日本十進分類法 | ||||||||||||
主題Scheme | NDC | |||||||||||
主題 | 007.642 | |||||||||||
ISSN | ||||||||||||
収録物識別子タイプ | PISSN | |||||||||||
収録物識別子 | 2327-5219 | |||||||||||
権利 | ||||||||||||
言語 | en | |||||||||||
権利情報 | Copyright © 2017 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). | |||||||||||
著者版フラグ | ||||||||||||
出版タイプ | VoR | |||||||||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
主となる版 | ||||||||||||
関連タイプ | isVersionOf | |||||||||||
識別子タイプ | URI | |||||||||||
関連識別子 | https://file.scirp.org/pdf/JCC_2017012215041977.pdf | |||||||||||
フォーマット | ||||||||||||
内容記述タイプ | Other | |||||||||||
内容記述 | application/pdf |