2010年
Bayesian X-ray computed tomography using material class knowledge
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
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- 開始ページ
- 2126
- 終了ページ
- 2129
- 記述言語
- 英語
- 掲載種別
- DOI
- 10.1109/icassp.2010.5495195
- 出版者・発行元
- IEEE
We propose a new reconstruction procedure for X-ray computed tomography (CT) based on Bayesian modeling. We utilize the knowledge that the human body is composed of only a limited number of materials whose CT values are roughly known in advance. Although the exact Bayesian inference of our model is intractable, we propose an efficient algorithm based on the variational Bayes technique. Experiments show that the proposed method performs better than the existing methods in severe situations where samples are limited or metal is inserted into the body.
- リンク情報
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- DOI
- https://doi.org/10.1109/icassp.2010.5495195
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000287096002027&DestApp=WOS_CPL
- URL
- http://xplorestaging.ieee.org/ielx5/5487364/5494886/05495195.pdf?arnumber=5495195
- ID情報
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- DOI : 10.1109/icassp.2010.5495195
- ISSN : 1520-6149
- Web of Science ID : WOS:000287096002027