Francois Meyer

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Because of the inherently low signal to noise ratio (SNR) of fMRI data, removal of low frequency signal intensity drift is an important preprocessing step, particularly in those brain regions that weakly activate. Two known sources of drift are noise from the MR scanner and aliasing of physiological pulsations. However, the amount and direction of drift is(More)
This work proposes a unified framework to track the deformation of the myocardium using velocity fields and boundary information. The deformation of the myocardium is characterized by a deforming mesh. A general framework for locally regularizing the velocity field has been developed. The tracking is modeled as an estimation problem which makes it possible(More)
We propose a new method to analyse seismic time-series and estimate the arrival times of seismic waves. Our approach combines two ingredients: the time-series are first lifted into a high-dimensional space using time-delay embedding; the resulting phase space is then parametrized using a non-linear method based on the eigenvectors of the graph Laplacian. We(More)
Functional Magnetic Resonance Imaging (fMRI) provides an unprecedented window into the complex functioning of the human brain, typically detailing the activity of thousands of voxels during hundreds of sequential time points. Unfortunately , the interpretation of fMRI is complicated due both to the relatively unknown connection between the hemodynamic(More)
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