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dc.contributor.advisorElfar Adalsteinsson.en_US
dc.contributor.authorCheng, Joseph Yitanen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2008-04-23T14:36:16Z
dc.date.available2008-04-23T14:36:16Z
dc.date.copyright2007en_US
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/41257
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.en_US
dc.descriptionIncludes bibliographical references (p. 53).en_US
dc.description.abstractSpecial magnetic resonance (MR) scans, such as spiral imaging and echo-planar imaging, require speed and gradient accuracy while putting high demands on the MR gradient system that may cause gradient distortion. Additionally, high field MR scans are prone to inhomogeneities that disturb the gradient system. Regardless of the source, gradient characterization provides a simple tool for distortion correction. An improved method, named the self-encoded slice selection algorithm, of characterizing the gradient system of the magnetic resonance system is proposed. It improves and combines the self-encode method and the direct slice selection method. The new approach is simple and fast, and allows for the measurement of waveform gradients that reach the system's limits. The technique is used to model the gradient system as a linear time-invariant transfer function through frequency-domain analysis and time-domain analysis. A transfer function model of the gradient system on the 3T Siemens Tim Trio scanner is presented here along with the characterization and analysis of common waveform gradients. Possible distortion correction approaches are also suggested.en_US
dc.description.statementofresponsibilityby Joseph Yitan Cheng.en_US
dc.format.extent53 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleGradient characterization in magnetic resonance imagingen_US
dc.title.alternativeGradient characterization in MRIen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc213413082en_US


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