Following the success of deep learning in a wide range of applications, neural network-
based machine-learning techniques have received significant interest for accelerating …

Purpose A calibrationless parallel imaging reconstruction method, termed simultaneous
autocalibrating and k‐space estimation (SAKE), is presented. It is a data‐driven, coil‐by‐coil …

We present \ell_1-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and
compressed sensing (CS) that permits an efficient implementation with clinically-feasible …

Purpose Phase‐constrained parallel MRI approaches have the potential for significantly
improving the image quality of accelerated MRI scans. The purpose of this study was to …

GRAPPA linearly combines the undersampled k‐space signals to estimate the missing k‐
space signals where the coefficients are obtained by fitting to some auto‐calibration signals …

A novel iterative k‐space data‐driven technique, namely parallel reconstruction using null
operations (PRUNO), is presented for parallel imaging reconstruction. In PRUNO, both data …

“Auto-calibrated” parallel imaging (PI) strategies provide a robust mechanism for
accelerating MRI acquisitions. However, most such strategies require the explicit formation …

In this paper, a calibrationless method is proposed for parallel magnetic resonance imaging
(pMRI). It is motivated by the observation that the gradients of the aliased images are jointly …

We focus on agent-based simulations where a large number of agents move in the space,
obeying to some simple rules. Since such kind of simulations are computational intensive, it …

In parallel magnetic resonance imaging (MRI), the problem is to reconstruct an image given
the partial K-space scans from all the receiver coils. Depending on its position within the …