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T-Space at The University of Toronto Libraries >
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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/26200

Title: MRI Based Imaging of Current Densities and Tissue Conductivities
Authors: Ma, Weijing
Advisor: Joy, Michael
Nachman, Adrian
Department: Electrical and Computer Engineering
Keywords: Current Density Imaging
Electrical properties
Magnetic Resonance Imaging
Current Density Impedance Imaging
Issue Date: 15-Feb-2011
Abstract: Magnetic resonance imaging (MRI) is an imaging modality that noninvasively measures magnetic fields by selectively exciting the magnetization of protons inside the body. When combined with an understanding of electromagnetic theory, MRI can be used in a novel way to provide a powerful tool for measuring the electromagnetic fields and electrical properties of biological tissues. This thesis presents the analytical, numerical, processing and experimental components of a successful implementation of Low-Frequency Current Density Impedance Imaging (LF-CDII), an impedance imaging method based on MRI measurements. The accuracy, stability and noise tolerance of this technique are examined. The first in-vivo LF-CDII experiment was conducted with a clinical MRI scanner, and the conductivity distribution of the heart of a live piglet was obtained. Both the simulation and experimental results show that LF-CDII can be used as a reliable tool for accurate noninvasive, quantitative imaging of tissue conductivities. This thesis also presents new data processing algorithms, imaging procedures and hardware development for the measurement of electromagnetic fields at radio frequencies, based on Polar Decomposition Radio Frequency Current Density Imaging (PD-RFCDI). The method was tested on both numerical models and experiments on phantoms. The results show that the techniques presented here are able to successfully image current density fields without the strict restrictions on the direction and magnitude of the currents required in previous versions of RFCDI.
URI: http://hdl.handle.net/1807/26200
Appears in Collections:Doctoral

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