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DC poleHodnotaJazyk
dc.contributor.authorYang, Bingxin
dc.contributor.authorYuan, Min
dc.contributor.authorMa, Yide
dc.contributor.authorZhang, Jiuwen
dc.contributor.editorSkala, Václav
dc.date.accessioned2016-01-07T09:51:32Z
dc.date.available2016-01-07T09:51:32Z
dc.date.issued2015
dc.identifier.citationJournal of WSCG. 2015, vol. 23, no. 1, p. 91-99.en
dc.identifier.issn1213–6972 (hardcopy)
dc.identifier.issn1213–6980 (CD-ROM)
dc.identifier.issn1213–6964 (online)
dc.identifier.urihttp://wscg.zcu.cz/WSCG2015/!_2015_Journal_WSCG-No-2.pdf
dc.identifier.urihttp://hdl.handle.net/11025/17158
dc.format9 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectkomprimované snímánícs
dc.subjectzobrazování magnetické rezonancecs
dc.subjecttransformace jednotného diskrétního zakřivenícs
dc.subjectvariabilní rozdělenícs
dc.subjectstřídavý směr metody multiplikátorůcs
dc.titleMagnetic resonance images reconstruction using uniform discrete curvelet transform sparse prior based compressed sensingen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedCompressed sensing(CS) has shown great potential in speeding up magnetic resonance imaging(MRI) without degrading images quality. In CS MRI, sparsity (compressibility) is a crucial premise to reconstruct high-quality images from non-uniformly undersampled k-space measurements. In this paper, a novel multi-scale geometric analysis method (uniform discrete curvelet transform) is introduced as sparse prior to sparsify magnetic resonance images. The generated CS MRI reconstruction formulation is solved via variable splitting and alternating direction method of multipliers, involving revising sparse coefficients via optimizing penalty term and measurements via constraining k-space data fidelity term. The reconstructed result is the weighted average of the two terms. Simulated results on in vivo data are evaluated by objective indices and visual perception, which indicate that the proposed method outperforms earlier methods and can obtain lower reconstruction error.en
dc.subject.translatedcompressed sensingen
dc.subject.translatedmagnetic resonance imagingen
dc.subject.translateduniform discrete curvelet transformen
dc.subject.translatedvariable splittingen
dc.subject.translatedalternating direction method of multipliersen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Volume 23, Number 2 (2015)

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Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam: http://hdl.handle.net/11025/17158

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  1. DSpace at University of West Bohemia
  2. Publikace ZČU / UWB Publications
  3. Časopisy ZČU / UWB Journals
  4. Journal of WSCG
  5. Volume 23 (2015)
  6. Volume 23, Number 2 (2015)