Purpose We examined magnetic field dependent SNR gains and ability to capture them with
multichannel receive arrays for human head imaging in going from 7 T, the most commonly …

This article introduces SuperVoxHenry, an inductance extraction simulator for analyzing
voxelized superconducting structures. SuperVoxHenry extends the capabilities of the …

Purpose Toward pushing the boundaries of ultrahigh fields for human brain imaging, we
wish to evaluate experimentally achievable SNR relative to ultimate intrinsic SNR (uiSNR) at …

As a promising data analysis technique, sparse modeling has gained widespread traction in
the field of image processing, particularly for image recovery. The matrix rank, served as a …

The approaches for tensor decomposition (TD) are reviewed in this study. For uncertainty
quantification and electromagnetic (EM) solvers, we cover their applications to surrogate …

Fast Fourier transform (FFT)-accelerated integral-equation-based electromagnetic (EM)
simulators have gained attraction for their capability to compute parasitics of arbitrarily …

Objective: We developed a hybrid volume surface integral equation (VSIE) method based on
domain decomposition to perform fast and accurate magnetic resonance imaging (MRI) …

Purpose To introduce a method for the estimation of the ideal current patterns (ICP) that
yield optimal signal‐to‐noise ratio (SNR) for realistic heterogeneous tissue models in MRI …

We investigated how to construct low-order subspace basis sets to accurately represent
electromagnetic (EM) fields generated within inhomogeneous arbitrary objects by radio …

High static field MR scanners can produce human tissue images of astounding clarity, but
rely on high frequency electromagnetic radiation that generates complicated in-tissue field …