Shahrum Nedjati-Gilani

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In this paper, we present a new regularized super-resolution method for finding accurate fibre orientations and volume fractions of fibre populations on a sub-voxel scale from a 3D diffusion MRI acquisition in order to distinguish between various fibre configurations such as fanning and bending, and ameliorate partial volume effects. We treat this task as a(More)
We present a new model for fanning and bending white matter structures on a sub-voxel scale. We devise a parametric model of how the fibre orientation varies spatially over each sub-voxel in the voxel grid for both types of configuration. Fitting the model provides quantitative information about the degree of fanning or bending in each voxel. We demonstrate(More)
This paper presents a new registration framework for quantifying myocardial motion and strain from the combination of multiple 3D ultrasound (US) sequences. The originality of our approach lies in the estimation of the transformation directly from the input multiple views rather than from a single view or a reconstructed compounded sequence. This allows us(More)
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