Fast robust dejitter and interslice discontinuity removal in MRI phase acquisitions: application to magnetic resonance elastography

buir.contributor.authorArıyürek, Cemre
dc.citation.epage1587en_US
dc.citation.issueNumber7en_US
dc.citation.spage1578en_US
dc.citation.volumeNumber38en_US
dc.contributor.authorBarnhill, E.en_US
dc.contributor.authorNikolova, M.en_US
dc.contributor.authorArıyürek, Cemreen_US
dc.contributor.authorDittmann, F.en_US
dc.contributor.authorBraun, J.en_US
dc.contributor.authorSack, I.en_US
dc.date.accessioned2020-02-04T13:09:29Z
dc.date.available2020-02-04T13:09:29Z
dc.date.issued2019-07
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractMRI phase contrast imaging methods that assemble slice-wise acquisitions into volumes can contain interslice phase discontinuities (IPDs) over the course of the scan from sources, including unavoidable physiological activity. In magnetic resonance elastography (MRE), this can alter wavelength and tissue stiffness estimates, invalidating the analysis. We first model this behavior as jitter along the z-axis of the phase of 3D complex-valued wave volumes. A two-step image processing pipeline is then proposed that removes IPDs. First, constant slicewise phase shift is removed with a novel, non-convex dejittering algorithm. Then, regional physiological noise artifacts are removed with novel filtering of 3D wavelet coefficients. Calibration of two pipeline coefficients, the dejitter parameter α and the wavelet band high-pass coefficient ωc , was first performed on a finite-element method brain phantom. A comparative investigation was then performed, on a cohort of 48 brain acquisitions, of four approaches to IPDs: 1) the proposed method; 2) a “control” condition of neglect of IPDs; 3) an anisotropic wavelet-based method; and 4) a method of in-plane (2D) processing. The present method showed medians of |G∗|=1873 Pa for a multifrequency wave inversion centered at 40 Hz which was within 6% of methods 3) and 4), while neglect produced |G∗| estimates a mean of 17% lower. The proposed method reduced the value range of the cohort against methods 3) and 4) by 29% and 31%, respectively. Such reduction in variance enhances the ability of brain MRE to predict subtler physiological changes. Our theoretical approach further enables more powerful applications of fundamental findings in noise and denoising to MRE.en_US
dc.description.provenanceSubmitted by Evrim Ergin (eergin@bilkent.edu.tr) on 2020-02-04T13:09:29Z No. of bitstreams: 1 Fast_Robust_Dejitter_and_Interslice_Discontinuity_Removal_in_MRI_Phase_Acquisitions_Application_to_Magnetic_Resonance_Elastography.pdf: 2019083 bytes, checksum: 3efa7cbf5b39f88e04e0b159f6fd220f (MD5)en
dc.description.provenanceMade available in DSpace on 2020-02-04T13:09:29Z (GMT). No. of bitstreams: 1 Fast_Robust_Dejitter_and_Interslice_Discontinuity_Removal_in_MRI_Phase_Acquisitions_Application_to_Magnetic_Resonance_Elastography.pdf: 2019083 bytes, checksum: 3efa7cbf5b39f88e04e0b159f6fd220f (MD5) Previous issue date: 2019-07en
dc.identifier.doi10.1109/TMI.2019.2893369en_US
dc.identifier.eissn1558-254X
dc.identifier.issn0278-0062
dc.identifier.urihttp://hdl.handle.net/11693/53057
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.1109/TMI.2019.2893369en_US
dc.source.titleIEEE Transactions on Medical Imagingen_US
dc.subjectMagnetic resonance imagingen_US
dc.subjectElastographyen_US
dc.subjectImage denoisingen_US
dc.titleFast robust dejitter and interslice discontinuity removal in MRI phase acquisitions: application to magnetic resonance elastographyen_US
dc.typeArticleen_US

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