– K. Niinimaki (University of Eastern Finland) : Functional magnetic resonance imaging and sparse sampling

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Date(s) - 7 novembre 2014

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Functional magnetic resonance imaging and sparse sampling by Kati Niinimaki (University of Eastern Finland)\n\nFunctional magnetic resonance imaging (fMRI) is a medical imaging method that can be used to gain information about brain activation. The correct detection and localization of brain activity both during a task or at rest can provide useful information for medical research purposes and for medical diagnosis. In order to be able to detect the rapid changes in the fMRI signal, the fMRI acquisition time needs to be short. However the image quality is related to the scanning time, since basically the more measurements one takes (i.e. longer scanning time) the better image quality one can expect. The MRI acquisition time could be significantly reduced by reducing the sampling rate of the k-space. Traditionally the k-space sampling pattern is designed to meet the Nyquist criterion and violation of this criterion causes artifact and deterioration in the image quality. In this research I shall consider some sparse recovery methods and study their applicability for fMRI purposes with sparsely sampled data.\n[