Drobnjak, Ivana; (2008) FMRI Simulator: Development and Applications. Doctoral thesis (D.Phil), University of Oxford.

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Abstract

Functional Magnetic Resonance Imaging (FMRI) is a non-invasive method of imaging brain function in-vivo. However, images produced in FMRI experiment almost invariably contain imperfections, known as artifacts. These artifacts can result from, for example, rigid-body motion of the head, magnetic field inhomogeneities, chemical shift and eddy currents. To investigate these artifacts, with the eventual aim of minimising or removing them completely, a computational model of the FMR image acquisition process was built which can simulate all of the above mentioned artifacts. The simulator uses a geometric definition of the object (brain), Bloch equations (to model the behaviour of the magnetisation) and a model for the Blood Oxygen Level Dependent (BOLD) activations. Furthermore, it simulates rigid-body motion of the object by solving Bloch equations for an object moving continuously in time (as opposed to assuming movement only between the acquisition of consecutive images). This is a novel approach in the area of MRI computer simulations. With this approach it is possible, in a controlled and precise way, to simulate the full effects of various rigid-body motion artifacts in FMRI data (e.g. spin-history effects, B0-motion interaction and within-scan motion blurring) and therefore formulate and test algorithms for their reduction. This thesis presents the development of the model for the simulator, its numerical implementation and solutions for the computational issues, and the validation of the simulator by comparing its outputs with existing theoretical and experimental results. Finally, the simulator is applied in a number of diverse applications. These applications include: comparing different acquisition techniques for eddy-current compensation; reproducing and extending experiments in neuronal current imaging; quantifying the performance of motion correction software; quantitatively evaluating the impact of stimulus correlated motion artifacts; and investigating the performance of Independent Component Analysis (ICA) as a tool for quantifying motion-related artifacts.

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