The work described in this thesis was conducted at the University of Nottingham in the Sir Peter Mansfield Imaging Centre, between September 2011 and 2014. Subject motion in high- resolution magnetic resonance imaging (MRI) is a major source of image artefacts. It is a very complex problem, due to variety of physical motion types, imaging techniques, or k-space trajectories. Many techniques have been proposed over the years to correct images for motion, all looking for the best practical solution in clinical scanning, which would give cost- effective, robust and high accuracy correction, without decreasing patient comfort or prolonging the scan time. Moreover, if the susceptibility induced field changes due to head rotation are large enough, they will compromise motion correction methods. In this work a method for prospective correction of head motion for MR brain imaging at 7 T was proposed. It would employ innovative NMR tracking devices not presented in literature before. The device presented in this thesis is characterized by a high accuracy of position measurements (0.06 ± 0.04 mm), is considered very practical, and stands the chance to be used in routine imaging in the future. This study also investigated the significance of the field changes induced by the susceptibility in human brain due to small head rotations (±10 deg). The size and location of these field changes were characterized, and then the effects of the changes on the image were simulated. The results have shown that the field shift may be as large as |-18.3| Hz/deg. For standard Gradient Echo sequence at 7 T and a typical head movement, the simulated image distortions were on average equal to 0.5%, and not larger than 15% of the brightest voxel. This is not likely to compromise motion correction, but may be significant in some imaging sequences.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:689971 |
| Date | January 2016 |
| Creators | Sulikowska, Aleksandra |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/33674/ |
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