MISC

2010年

Bayesian X-ray computed tomography using material class knowledge

2010 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Wataru Fukuda
  • ,
  • Shin-ichi Maeda
  • ,
  • Atsunori Kanemura
  • ,
  • Shin Ishii

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
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
  • DOI : 10.1109/icassp.2010.5495195
  • ISSN : 1520-6149
  • Web of Science ID : WOS:000287096002027

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