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dc.contributor.advisorBilgin, Ali
dc.contributor.authorKeerthivasan, Mahesh Bharath
dc.creatorKeerthivasan, Mahesh Bharath
dc.date.accessioned2019-09-17T22:42:24Z
dc.date.available2019-09-17T22:42:24Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10150/634433
dc.description.abstractMagnetic Resonance Elastography (MRE) is a non-invasive imaging technique used to determine the elastic properties of biological tissues. It can be used to aid the diagnosis of pathologies (such as tumors and fibrosis) which result in the variation of tissue stiffness. In this thesis, a MR elastography system was developed for use in a clinical setting. A pressure-based longitudinal driver was built to generate the shear waves. An elastography pulse sequence with motion encoding gradients was designed based on the gradient-echo and the spin-echo sequences. The pulse sequence included the ability to switch the motion encoding along any of the three coordinate axes depending on the direction of motion to be measured. Wave images were obtained by acquiring phase data for different time offsets in the motion cycle. An elastogram was computed from the phase data using the Local Frequency Estimation (LFE) algorithm. The validity of the method was experimentally verified using silicone and agar gel phantoms of varying stiffnesses. The performance of the gradient-echo and spin-echo sequences were investigated for different motion encoding gradient parameters.en_US
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectmagnetic resonance elastographyen_US
dc.titleLONGITUDINAL DRIVER BASED MAGNETIC RESONANCE ELASTOGRAPHYen_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.nameM.S.en_US
refterms.dateFOA2019-09-17T22:42:25Z


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