Efficient parameter mapping for magnetic resonance imaging

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buir.advisorÇukur, Tolga
dc.contributor.authorKeskin, Kübra
dc.date.accessioned2019-08-16T09:35:20Z
dc.date.available2019-08-16T09:35:20Z
dc.date.copyright2019-07
dc.date.issued2019-07
dc.date.submitted2019-08-05
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.) : Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2019.en_US
dc.descriptionIncludes bibliographical references (leaves 58-62).en_US
dc.description.abstractBalanced steady-state free precession (bSSFP) is a magnetic resonance imaging (MRI) sequence that enables high signal-to-noise ratios in short scan times. However, it has elevated sensitivity to main eld inhomogeneity, which leads to banding artifacts near regions of relatively large o -resonance shifts. To suppress these artifacts, multiple bSSFP images of the same anatomy are commonly acquired with a set of di erent RF phase-cycling increments. Joint processing of phase-cycled acquisitions has long been employed to eliminate banding artifacts due to eld inhomogeneity. Multiple bSSFP acquisitions can be further used for parameter mapping by exploiting the signal model of phase-cycled bSSFP. While model based approaches for mapping are e ective, they often need a large number of acquisitions, inherently limiting scan e ciency. In this thesis, we propose a new method for parameter mapping with improved e ciency and accuracy in phasecycled bSSFP MRI. The proposed method is based on the elliptical signal model framework for complex bSSFP signals; and introduces an observation about the signal's geometry to the constrained parameter mapping problem, such that the number of unknowns and thereby the required number of acquisitions can be reduced. It also leverages dictionary-based identi cation to improve estimation accuracy. Simulated, phantom and in vivo experiments demonstrate that the proposed method enables improved parameter mapping with fewer acquisitions.en_US
dc.description.degreeM.S.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2019-08-16T09:35:20Z No. of bitstreams: 1 10278963.pdf: 9804015 bytes, checksum: 1e348f28ab77843bee292a55b0e05e97 (MD5)en
dc.description.provenanceMade available in DSpace on 2019-08-16T09:35:20Z (GMT). No. of bitstreams: 1 10278963.pdf: 9804015 bytes, checksum: 1e348f28ab77843bee292a55b0e05e97 (MD5) Previous issue date: 2019-08en
dc.description.statementofresponsibilityby Kübra Keskinen_US
dc.embargo.release2020-02-05
dc.format.extentxvi, 62 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB156517
dc.identifier.urihttp://hdl.handle.net/11693/52342
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMagnetic resonance imaging (MRI)en_US
dc.subjectBalanced SSFPen_US
dc.subjectPhase-cyclingen_US
dc.subjectParameter mappingen_US
dc.subjectEllipse ttingen_US
dc.subjectConstrained optimizationen_US
dc.titleEfficient parameter mapping for magnetic resonance imagingen_US
dc.title.alternativeManyetik rezonans görüntüleme için verimli parametre haritalamasıen_US
dc.typeThesisen_US

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Dept. of Electrical and Electronics Engineering - Master's degree