A Henning

This paper compares deep learning models for improving 1H MRSI reconstruction, finding that U-Net outperforms MultiNet in reducing lipid artifacts and improving metabolite map fidelity.

This study evaluates the performance of higher-order B0 shim systems in 7T MRI systems, finding that second- and third-order shim coils introduce impurities that reduce B0 field homogeneity and effectiveness.

OmniShim improves B0 magnetic field homogeneity across MRI systems, enhancing image quality and spectral resolution in various applications.

ProFit-1D was adapted to fit J-difference edited spectra at 3T and showed higher accuracy and precision than existing software for estimating metabolite concentrations.

This paper introduces a novel 2D J-resolved metabolite-cycled semiLASER spectroscopy method to quantify 16 metabolites in the human brain at 9.4 T, demonstrating improved sensitivity and reduced acquisition time.

This paper quantifies metabolite concentrations in the human cerebrum using 9.4T 1H MRSI data and derives region-specific concentrations through group averaging.

The paper measures glutamate metabolism in the human brain using 1H FID-MRSI after oral administration of [1-13C]Glc, revealing labeling changes in multiple metabolites with high spatial and temporal resolution.

This paper presents quantitative metabolite maps of 12 metabolites in human brains at 9.4 T, using voxel-specific T1-relaxation corrections for water and metabolites.

The paper demonstrates a method to estimate 31P transversal relaxation times and metabolite concentrations in the human brain at 9.4T, finding T2 values and pH levels consistent with literature.

The paper evaluates how lipid suppression, macromolecular models, and baseline stiffness affect reproducibility of metabolite ratios in human brain MRSI data at 9.4 T.

The paper compares two techniques for measuring glucose metabolism in the human brain using deuterium-labeled compounds and MR spectroscopy, estimating TCA cycle and glutamine synthesis rates.