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Improved magnetic resonance chemical shift imaging at 3 Tesla using a 32-channel integrated RF-shim coil array

Author(s)
Kızıldağ, Eren C
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Elfar Adalsteinsson.
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MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
In vivo chemical shift imaging is an imaging modality which uses the so-called chemical-shift phenomenon to quantitate brain metabolites spatially, therefore renders the study of brain metabolism and neurodegenerative diseases possible and eases diagnosis of tumors. However, the method is highly vulnerable to local main magnetic field (Bo) inhomogeneities arising from magnetic susceptibility differences which is predominantly present in air-tissue interfaces. Such magnetic field inhomogeneities result in number of imaging artifacts including chemical shift displacement of metabolites, spectral line broadening as well as complicated water and lipid suppression; which reduce spectral quality. The main goal of this work is to compensate Bo imperfections and therefore mitigate aforementioned artifacts to earn enhanced spectral quality with the aid of a recently introduced, novel, 32-channel integrated RF-shim coil hardware. Experimental results indeed demonstrate sharper spectral lines with narrower line widths and improved water suppression performance in the regions with poor BO conditions with the application of the shim coil hardware.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 87-93).
 
Date issued
2017
URI
http://hdl.handle.net/1721.1/108976
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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