نبذة مختصرة : This dissertation is devoted to the exploration of novel imaging methods for functional and diffusion magnetic resonance imaging at ultra-high field strengths, particularly targeting at human in vivo applications at 9.4 Tesla.In the first part of this work the principles of nuclear magnetic resonance (NMR) and the basics of magnetic resonance imaging (MRI) are introduced. This is followed by a brief overview of two specialised imaging methods that nowadays find wide application in clinical and research routine: functional magnetic resonance imaging (fMRI) and diffusion magnetic resonance imaging (dMRI), specifically diffusion tensor imaging (DTI) and q-ball imaging (QBI).Part two and three of this work give a comprehensive overview of the self-contained implementations, simulations, experiments and findings carried out and made in the context of this work. Part two has a very close focus on the yet unsolved problem of analytically defining an isotropic distribution of direction vectors. Among various scientific disciplines this problem is common to DTI, QBI and other high angular resolution diffusion imaging (HARDI) methods, which today still greatly rely on numerically precomputed look-up tables. To provide more experimental flexibility a novel deterministic sampling scheme is developed and shown to achieve results as isotropic as the numerical gold standard. To prove this, exhaustive DTI Monte Carlo simulations as well as single- and multi-fibre QBI simulations are performed. The systematic analysis of DTI and QBI estimation errors made as a function of simulated fibre direction provides novel insights into the importance of sampling isotropy in QBI.The third and final part of this work is devoted to the development and implementation of suit- able MRI pulse sequences for ultra-high field (UHF) applications, in particular for fMRI and dMRI. Latest findings and considerations with regard to an alternative single-shot dMRI technique based on stimulated echoes are discussed and the applicability at UHF is ...
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