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dc.contributor.authorÇukur, T.en_US
dc.date.accessioned2016-02-08T10:32:30Z
dc.date.available2016-02-08T10:32:30Z
dc.date.issued2015en_US
dc.identifier.issn0278-0062
dc.identifier.urihttp://hdl.handle.net/11693/24658
dc.description.abstractBalanced steady-state free precession (SSFP) imaging suffers from irrecoverable signal losses, known as banding artifacts, in regions of large B0 field inhomogeneity. A common solution is to acquire multiple phase-cycled images each with a different frequency sensitivity, such that the location of banding artifacts are shifted in space. These images are then combined to alleviate signal loss across the entire field-of-view. Although high levels of artifact suppression are viable using a large number of images, this is a time costly process that limits clinical utility. Here, we propose to accelerate individual acquisitions such that the overall scan time is equal to that of a single SSFP acquisition. Aliasing artifacts and noise are minimized by using a variable-density random sampling pattern in k-space, and by generating disjoint sampling patterns for separate acquisitions. A sparsity-enforcing method is then used for image reconstruction. Demonstrations on realistic brain phantom images, and in vivo brain and knee images are provided. In all cases, the proposed technique enables robust SSFP imaging in the presence of field inhomogeneities without prolonging scan times. © 2014 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleIEEE Transactions on Medical Imagingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/TMI.2014.2346814en_US
dc.subjectBanding artifacten_US
dc.subjectCompressed sensingen_US
dc.subjectMagnetic resonance imaging (MRI)en_US
dc.subjectPhase cyclingen_US
dc.subjectRandom undersamplingen_US
dc.subjectSteady - state free precession (SSFP)en_US
dc.subjectVariable densityen_US
dc.subjectCompressed sensingen_US
dc.subjectSignal reconstructionen_US
dc.subjectBanding artifacten_US
dc.subjectPhase cyclingen_US
dc.subjectRandom under samplingsen_US
dc.subjectSteady state free precessionsen_US
dc.subjectVariable densityen_US
dc.subjectMagnetic resonance imagingen_US
dc.subjectAccelerationen_US
dc.subjectArtifact reductionen_US
dc.subjectBrain sizeen_US
dc.subjectDensityen_US
dc.subjectGray matteren_US
dc.subjectImage qualityen_US
dc.subjectImage reconstructionen_US
dc.subjectImagingen_US
dc.subjectNeuroimagingen_US
dc.subjectNuclear magnetic resonance imagingen_US
dc.subjectPhantomen_US
dc.subjectRadiological proceduresen_US
dc.subjectSignal noise ratioen_US
dc.subjectSteady state free precession imagingen_US
dc.subjectWhite matteren_US
dc.subjectAlgorithmen_US
dc.subjectAnatomy and histologyen_US
dc.subjectImage processingen_US
dc.subjectKneeen_US
dc.subjectProceduresen_US
dc.subjectAlgorithmsen_US
dc.subjectArtifactsen_US
dc.subjectBrainen_US
dc.subjectHumansen_US
dc.subjectImage Processing, Computer-Assisteden_US
dc.subjectMagnetic Resonance Imagingen_US
dc.subjectPhantomsen_US
dc.subjectSignal - To - Noise Ratioen_US
dc.titleAccelerated phase-cycled SSFP imaging with compressed sensingen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage107en_US
dc.citation.epage115en_US
dc.citation.volumeNumber34en_US
dc.citation.issueNumber1en_US
dc.identifier.doi10.1109/TMI.2014.2346814en_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US


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