Biomedical applications of sodium MRI in vivo
G Madelin, RR Regatte - Journal of Magnetic Resonance …, 2013 - Wiley Online Library
In this article we present an up‐to‐date overview of the potential biomedical applications of
sodium magnetic resonance imaging (MRI) in vivo. Sodium MRI is a subject of increasing …
sodium magnetic resonance imaging (MRI) in vivo. Sodium MRI is a subject of increasing …
Sodium MRI: methods and applications
Sodium NMR spectroscopy and MRI have become popular in recent years through the
increased availability of high-field MRI scanners, advanced scanner hardware and improved …
increased availability of high-field MRI scanners, advanced scanner hardware and improved …
Accelerated MR parameter mapping with low‐rank and sparsity constraints
Purpose To enable accurate magnetic resonance (MR) parameter mapping with accelerated
data acquisition, utilizing recent advances in constrained imaging with sparse sampling …
data acquisition, utilizing recent advances in constrained imaging with sparse sampling …
P‐LORAKS: low‐rank modeling of local k‐space neighborhoods with parallel imaging data
Purpose To propose and evaluate P‐LORAKS a new calibrationless parallel imaging
reconstruction framework. Theory and Methods LORAKS is a flexible and powerful …
reconstruction framework. Theory and Methods LORAKS is a flexible and powerful …
Compressed sensing dynamic cardiac cine MRI using learned spatiotemporal dictionary
Y Wang, L Ying - IEEE transactions on Biomedical Engineering, 2013 - ieeexplore.ieee.org
In dynamic cardiac cine magnetic resonance imaging, the spatiotemporal resolution is
limited by the low imaging speed. Compressed sensing (CS) theory has been applied to …
limited by the low imaging speed. Compressed sensing (CS) theory has been applied to …
Fast data-driven learning of parallel MRI sampling patterns for large scale problems
In this study, a fast data-driven optimization approach, named bias-accelerated subset
selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the …
selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the …
New theory and faster computations for subspace-based sensitivity map estimation in multichannel MRI
Sensitivity map estimation is important in many multichannel MRI applications. Subspace-
based sensitivity map estimation methods like ESPIRiT are popular and perform well …
based sensitivity map estimation methods like ESPIRiT are popular and perform well …
Linear predictability in magnetic resonance imaging reconstruction: Leveraging shift-invariant Fourier structure for faster and better imaging
JP Haldar, K Setsompop - IEEE Signal Processing Magazine, 2020 - ieeexplore.ieee.org
Magnetic resonance imaging (MRI) is a powerful and highly versatile imaging technique that
has had a tremendous impact in both science and medicine. Unfortunately, MRI data …
has had a tremendous impact in both science and medicine. Unfortunately, MRI data …
DeepSENSE: Learning coil sensitivity functions for SENSE reconstruction using deep learning
Purpose To improve the estimation of coil sensitivity functions from limited auto‐calibration
signals (ACS) in SENSE‐based reconstruction for brain imaging. Methods We propose to …
signals (ACS) in SENSE‐based reconstruction for brain imaging. Methods We propose to …
Accelerated exponential parameterization of T2 relaxation with model‐driven low rank and sparsity priors (MORASA)
Purpose This work is to develop a novel image reconstruction method from highly
undersampled multichannel acquisition to reduce the scan time of exponential …
undersampled multichannel acquisition to reduce the scan time of exponential …