Dynamic MRI Using SmooThness Regularization on Manifolds (SToRM)

Accelerated dynamic MRI using patch regularization for implicit motion compensation.

PURPOSE To introduce a fast algorithm for motion-compensated accelerated dynamic MRI. METHODS An efficient patch smoothness regularization scheme, which implicitly compensates for inter-frame motion, is introduced to recover dynamic MRI data from highly undersampled measurements. The regularization prior is a sum of distances between each rectangular patch in the dataset with other patches in...

Motion-Adaptive Spatio-Temporal Regularization (MASTeR) for Accelerated Dynamic MRI

Accelerated MRI techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated MRI is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped for...

Smoothness of Isometries between Subriemannian Manifolds

Abstract In a joint work with Enrico Le Donne (Jyvaskyla, Finland) we show that the group of isometries (i.e., distance-preserving homeomorphisms) of an equiregular subRiemannian manifold is a finitedimensional Lie group of smooth transformations. The proof is based on a new PDE argument, in the spirit of harmonic coordinates, establishing that in an arbitrary subRiemannian manifold there exist...

Accelerated dynamic MRI Using Patch Regularization for Implicit motion CompEnsation (PRICE)

Purpose: To introduce a fast algorithm for motion-compensated accelerated dynamic MRI. Methods: An efficient patch smoothness regularization scheme, which implicitly compensates for interframe motion, is introduced to recover dynamic MRI data from highly undersampled measurements. The regularization prior is a sum of distances between each rectangular patch in the dataset with other patches in ...

On the Regularization of Dynamic