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Mixture of competitive linear models for phased-array magnetic resonance imagin
Dept. of ECE, University of Florida, USA.
Dept. of ECE, University of Florida, USA.
Dept. of ECE, The George Washington University, USA.
Dept. of ECE, University of Florida, USA.
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2004 (English)In: 2004 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),  Vol. 5, 2004, V-585-V-588 p.Conference paper, Published paper (Refereed)
Abstract [en]

Phased-array magnetic resonance imaging is an important contemporary research field in terms of the expected clinical gains in medical imaging technology. Recent research focused on heuristic coil image recombination methods as well as statistical signal processing approaches. In this paper, we investigate the performance of an adaptive signal processing approach, namely mixture of competitively trained models. The proposed method has the ability to train on a set of images and generalize its performance to previously unseen images. Performance evaluations on real data validate the effectiveness of this method.

Place, publisher, year, edition, pages
2004. V-585-V-588 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-77274DOI: 10.1109/ICASSP.2004.1327178ISBN: 0-7803-8484-9 (print)OAI: oai:DiVA.org:liu-77274DiVA: diva2:526071
Conference
ICASSP 2004, 17-21 May 2004, Montreal, Quebec, Canada
Available from: 2012-05-10 Created: 2012-05-10 Last updated: 2012-05-16Bibliographically approved

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Larsson, Erik G.

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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  • asciidoc
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