Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of target
anatomy, surrounding tissue, and instrumentation, but there are significant challenges in …

Various techniques have been proposed which aim at scan time reduction and/or at
improved image quality by increasing the spatial resolution. Compressed sensing (CS) …

Tomographic image reconstruction is generally an ill-posed linear inverse problem. Such ill-
posed inverse problems are typically regularized using prior knowledge of the sought-after …

Purpose: To improve the quality of images obtained via dynamic contrast enhanced MRI
(DCE-MRI), which contain motion artifacts and blurring using a deep learning approach …

Purpose To demonstrate the utility of compressed sensing with parallel imaging
(Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging …

Objectives Acceleration of MR sequences beyond current parallel imaging techniques is
possible with the Compressed SENSE technique that has recently become available for 1.5 …

The U-net is a deep-learning network model that has been used to solve a number of
inverse problems. In this work, the concatenation of two-element U-nets, termed the W-net …

Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is
informative and important to understand motion mechanisms of body regions. Modeling …

Objective The aim of this study was to evaluate the clinical feasibility of fast 3-dimensional
(3D) magnetic resonance cholangiopancreatography (MRCP) using compressed sensing …

The relevant clinical accelerated magnetic resonance techniques that are available currently
for routine patient examinations are reviewed, presenting and discussing the benefits …