Compressed sensing (CS) has been demonstrated to accelerate MRI acquisitions by reconstructing sparse images of good quality from highly undersampled data. Motion during MR scans can cause inconsistencies in k-space data, resulting in strong motion artifacts in the reconstructed images. For CS to be useful in these applications, motion correction techniques need to be combined with the undersam...

INTRODUCTION Functional Magnetic Resonance Imaging (fMRI) is being used extensively in neuroscientific studies and is entering the clinical field. Due to its low inherent effect to noise ratio even at high field strength the results are often compromised by adverse events during the acquisition. The most frequent cause of signal fluctuations that degrade the detection of paradigm induced neuron...

Introduction: In functional MRI (fMRI), the presence of subject motion during the acquisition of an image series can confound results. In general practice, only the magnitude portion of the images is used in the functional analysis [1], and thus correction for subject motion is required in only the magnitude images. However, statistical models for performing complex-valued fMRI analysis are ava...

PURPOSE Conventional motion and eddy-current correction, where each diffusion-weighted volume is registered to a non diffusion-weighted reference, suffers from poor accuracy for high b-value data. An alternative approach is to extrapolate reference volumes from low b-value data. We aim to compare the performance of conventional and extrapolation-based correction of diffusional kurtosis imaging ...

OBJECTIVES Contrast-enhanced ultrasound (CEUS) cines of focal liver lesions (FLLs) can be quantitatively analyzed to measure tumor perfusion on a pixel-by-pixel basis for diagnostic indication. However, CEUS cines acquired freehand and during free breathing cause nonuniform in-plane and out-of-plane motion from frame to frame. These motions create fluctuations in the time-intensity curves (TICs...