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dc.contributor.authorIlıcak, Efeen_US
dc.contributor.authorÇetin, S.en_US
dc.contributor.authorSarıtaş, Emine Ülküen_US
dc.contributor.authorÜnal, G.en_US
dc.contributor.authorÇukur, Tolgaen_US
dc.coverage.spatialZonguldak, Turkeyen_US
dc.date.accessioned2018-04-12T11:48:45Z
dc.date.available2018-04-12T11:48:45Z
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/11693/37711
dc.descriptionDate of Conference: 16-19 May 2016en_US
dc.descriptionConference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016en_US
dc.description.abstractThe image quality of unenhanced magnetic resonance angiography, which images blood vessels without contrast agents, is limited by constraints related to scan time. To address this problem, techniques that undersample angiographic data and then apply regularized reconstructions are used. Conventional reconstructions employ regularization terms with uniform spatial weighting. Thus, they can yield improper suppression of aliasing artifacts and poor blood/background contrast. In this study, a reconstruction strategy is evaluated that applies spatially-adaptive regularization based on vessel maps obtained via a tractographic segmentation. This strategy is compared with conventional methods in terms of peak signal to noise ratio, structural similarity and contrast.en_US
dc.language.isoTurkishen_US
dc.source.titleProceedings of the IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2016.7495806en_US
dc.subjectMagnetic resonance angiographyen_US
dc.subjectReconstructionen_US
dc.subjectSegmentationen_US
dc.subjectUnenhanceden_US
dc.subjectVasculatureen_US
dc.titleAdaptive reconstruction for vessel preservation in unenhanced MR angiographyen_US
dc.title.alternativeKontrast maddesiz anjiyografide damar korunumu için uyarlanmış geriçatımen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentNational Magnetic Resonance Research Center (UMRAM)en_US
dc.citation.spage577en_US
dc.citation.epage580en_US
dc.identifier.doi10.1109/SIU.2016.7495806en_US
dc.publisherIEEEen_US


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