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Dissertation Defense

Topics in steady-state MRI sequences and RF pulse optimization

Hao Sun

Magnetic resonance imaging (MRI) relies on a properly designed sequence of time-varying radio frequency (RF) and gradient fields to 'excite' an imaging region inside the human body. In this work, we propose two novel methods for optimizing the RF and gradient pulses. First, we propose a minimax formulation that directly controls the maximum excitation error, and an effective algorithm using variable splitting and alternating direction method of multipliers (ADMM). Our method reduced the maximum excitation by more than half in all our testing cases. Second, we proposed a method that jointly optimizes the gradient and RF pulses, leading to at least 40 percent lower normalized root-mean-square error (NRMSE) than existing pulse designs. In addition to RF pulse optimization, we also investigate several aspects of a recently proposed steady-state MRI sequence named small- tip fast recovery (STFR). We first demonstrate that STFR can reliably detect functional MRI signal. We also combine our proposed optimized RF pulse with STFR to produce a new 'zoomed MRI' sequence for rapid imaging of a reduced field-of-view, which may have application in, e.g., high resolution functional MRI.

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