Multiparametric quantitative imaging is gaining increasing interest due to its widespread
advantages in clinical applications. Magnetic resonance fingerprinting is a recently …

Quantitative mapping of MR tissue parameters such as the spin‐lattice relaxation time (T1),
the spin‐spin relaxation time (T2), and the spin‐lattice relaxation in the rotating frame (T1ρ) …

Quantitative cardiovascular magnetic resonance (CMR) imaging can be used to
characterize fibrosis, oedema, ischaemia, inflammation and other disease conditions …

Multi-institutional efforts can facilitate training of deep MRI reconstruction models, albeit
privacy risks arise during cross-site sharing of imaging data. Federated learning (FL) has …

Purpose The proposed reconstruction framework addresses the reconstruction accuracy,
noise propagation and computation time for magnetic resonance fingerprinting. Methods …

Purpose A new acquisition and reconstruction method called T2 Shuffling is presented for
volumetric fast spin‐echo (three‐dimensional [3D] FSE) imaging. T2 Shuffling reduces …

Purpose This article introduces a constrained imaging method based on low‐rank and
subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). Theory …

Compressed sensing (CS) has exhibited great potential for accelerating magnetic
resonance imaging (MRI). In CS-MRI, we want to reconstruct a high-quality image from very …

Magnetic resonance (MR) fingerprinting is a new quantitative imaging paradigm, which
simultaneously acquires multiple MR tissue parameter maps in a single experiment. In this …

High-dimensional MR imaging often requires long data acquisition time, thereby limiting its
practical applications. This paper presents a low-rank tensor based method for accelerated …