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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Improvements in Diffusion Weighted Imaging Through a Composite Body and Insert Gradient Coil System

Jepsen, Peter Austin 10 July 2013 (has links) (PDF)
Diffusion Magnetic Resonance Imaging (DMRI) is a class of Magnetic Resonance Imaging (MRI) techniques with broad medical applications ranging from characterization of tumors and brain damage to potential prediction of stroke. Gradient coil and signal-to- noise ratio (SNR) constraints limit spatial resolution, accuracy, and scan time in DMRI. Achieving high b-values (measures of a scan's sensitivity to diffusion) often require scans with long diffusion gradient pulses, leading to significant magnetic resonance (MR) signal decay before the signal can be sampled. This signal loss reduces the accuracy of diffusion parameter estimation. The ability to sample the MR signal sooner while maintaining the same b-value is restricted by the maximum amplitude and slew rate of gradient coils. A composite system utilizing body and high-powered insert gradient coils can achieve high b-values more quickly, enabling a shorter delay between excitation and signal sampling and improved accuracy of diffusion parameter estimation. Alternately, such a system can achieve higher b-values at an equivalent delay between excitation and signal sampling. This thesis describes the implementation of such a system, experiment design for evaluating the benefits of the system to DMRI, and design of a diffusion phantom. Also included are a characterization of a composite system's improvements to DMRI based on analysis of experimentally-obtained data and simulation results validating those findings. Finally, recommendations for further improvements to diffusion MRI are given.

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