Date of Award
Cell tracking, Coherence pathways, Compressed sensing, MRI, Optimization, Partition method
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Magnetic Resonance Imaging (MRI) is a non-invasive imaging modality with numerous applications due to its flexible contrast and high resolution. Recent improvements in computation power have enabled optimizations which were previously out of reach. This has led to improvements in image reconstruction and experiment design.
Compressed sensing (CS) allows for images to be reconstructed using less data than is normally required leading to faster image acquisitions. In this thesis, CS is applied to experiments tracking individual cells in time lapse MRI. The faster image acquisition with CS reduces blurring from cell motion, improving the Contrast-to-Noise ratio (CNR) of moving cells and allows faster cells to be detected.
Pi Echo Planar Imaging (PEPI) is an MRI pulse sequence that allows high resolution images to be acquired quickly with relatively low gradient duty cycle. Low field applications benefit significantly from low gradient duty cycle as it reduces concomitant magnetic field artifacts, so PEPI is an attractive option for affordable low field scanners. However, there are challenges in implementing PEPI, due to its high requirement on the flip angle of the π RF pulses. Deviation of the flip angle causes coherence pathway artifacts restricting PEPI to small samples in the homogeneous region of the RF coil and preventing 2D slice selective experiment. In this thesis, the coherence pathway artifacts are addressed using an optimized phase cycling scheme, reducing the flip angle sensitivity, and enabling a slice selective PEPI sequence.
Armstrong, Mark, "Optimization in MRI Experiment Design and Image Reconstruction" (2023). Electronic Theses and Dissertations. 8966.