… of parallel imaging methods for the reconstruction of accelerated non-Cartesian data. Parallel
imaging … parallel imaging, three representative methods that span the various types of …

… MRIs. In this paper, we show that a novel combination of classical parallel imaging techniques
with deep neural networks can … Utilizing parallel imaging in deep learning approaches to …

… in parallel imaging, a class of image reconstruction techniques for shortening scan time. First,
the fundamentals of MRI … in parallel imaging, a class of image reconstruction methods that …

… In this work we present an approach to employ regularization in reconstructing parallel MRI
data in order to reduce the noise amplification of the reconstruction (g-factor). The proposed L…

… , eg in terms of reconstruction fidelity and noise behavior. … reconstruction task. The purpose
of the present paper is to review the basic approaches to parallel imaging reconstruction in …

… factor for routine clinical applications of MRI. One of the most … MRI scan time during the past
20 years was parallel imaging [… to improve the reconstruction quality in parallel imaging MRI. …

… (10), who proposed a k-space-based reconstruction of subsampled 3D parallel imaging …
data points are reconstructed by applying two separate 1D-GRAPPA reconstruction steps along …

… One of several parallel imaging algorithms can then be used to reconstruct artifact-free …
concepts of parallel imaging and explains how it has been implemented on clinical MRI scanners…

… been experimenting with applying compressed sensing parallel imaging for body imaging of
… -SPIRiT, an iterative autocalibrating parallel imaging reconstruction that enforces both data …

… Conventional Parallel Imaging reconstruction resolved as gradient descent steps was
compacted as network layers and interleaved with convolutional layers in a general convolutional …