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dc.contributor.advisorElfar Adalsteinsson.en_US
dc.contributor.authorGagoski, Borjan Aleksandaren_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2007-07-18T13:12:16Z
dc.date.available2007-07-18T13:12:16Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/37930
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.en_US
dc.descriptionIncludes bibliographical references (p. 71-73).en_US
dc.description.abstractConventional Magnetic Resonance Spectroscopic Imaging (MRSI) suffers from both low signal-to-noise (SNR), as well as long acquisition times. The development of high-fidelity gradient coils has opened opportunities for fast k-space encoding schemes that are already used in structural imaging. At the same time, receive-coil arrays using 4 and 23 channels have been developed and reported to produce improved SNR over conventional quadrature detection by single coils. Fast spectroscopic imaging algorithm using spiral k-space trajectories and multiple-channel coil arrays is proposed in order to overcome the long acquisition-time limitations of conventional MRSI.en_US
dc.description.statementofresponsibilityby Borjan Aleksandar Gagoski.en_US
dc.format.extent73 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/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleFast magnetic resonance spectroscopic imaging using RF coil arraysen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc136941124en_US


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