Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

The mechanical functions of muscles involve the generation of force and the actuation of
movement by shortening or lengthening under load. These functions are influenced, in part …

Diffusion Weighted Images (DWI) normally shows a low Signal to Noise Ratio (SNR) due to
the presence of noise from the measurement process that complicates and biases the …

Recent theoretical results on low-rank matrix reconstruction have inspired significant interest
in low-rank modeling of MRI images. Existing approaches have focused on higher …

This paper proposes a novel method for MRI denoising that exploits both the sparseness
and self-similarity properties of the MR images. The proposed method is a two-stage …

Purpose To accelerate spectroscopic imaging using sparse sampling of‐space and
subspace (or low‐rank) modeling to enable high‐resolution metabolic imaging with good …

Diffusion weighted imaging (DWI) is used to study white-matter fibre organisation,
orientation and structural connectivity by means of fibre reconstruction algorithms and …

Purpose To obtain high‐sensitivity CEST maps by exploiting the spatiotemporal correlation
between CEST images. Methods A postprocessing method accomplished by multilinear …

Diffusion magnetic resonance imaging (MRI) datasets suffer from low Signal-to-Noise Ratio
(SNR), especially at high b-values. Acquiring data at high b-values contains relevant …

Purpose We evaluate a new approach for achieving diffusion MRI data with high spatial
resolution, large volume coverage, and fast acquisition speed. Theory and Methods A recent …