A sparse model-inspired deep thresholding network for exponential signal reconstruction—Application in fast biological spectroscopy

Z Wang, D Guo, Z Tu, Y Huang, Y Zhou… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
The nonuniform sampling (NUS) is a powerful approach to enable fast acquisition but
requires sophisticated reconstruction algorithms. Faithful reconstruction from partially …

Variational mode decomposition for NMR echo data denoising

J Guo, R Xie, Y Wang, L Xiao, J Fu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Nuclear magnetic resonance (NMR) relaxometry, a noninvasive and nondestructive method,
is a key technique for unconventional reservoir evaluation. Echo data detected from NMR …

Exponential signal reconstruction with deep Hankel matrix factorization

Y Huang, J Zhao, Z Wang, V Orekhov… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Exponential function is a basic form of temporal signals, and how to fast acquire this signal is
one of the fundamental problems and frontiers in signal processing. To achieve this goal …

Machine learning-enabled high-resolution dynamic deuterium MR spectroscopic imaging

Y Li, Y Zhao, R Guo, T Wang, Y Zhang… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Deuterium magnetic resonance spectroscopic imaging (DMRSI) has recently been
recognized as a potentially powerful tool for noninvasive imaging of brain energy …

An automatic denoising method for NMR spectroscopy based on low-rank Hankel model

T Qiu, W Liao, Y Huang, J Wu, D Guo… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Nuclear magnetic resonance (NMR) spectroscopy, whose time domain data is modeled as
the sum of damped exponential signals, has become an indispensable tool in various …

Deep learning can accelerate and quantify simulated localized correlated spectroscopy

Z Iqbal, D Nguyen, MA Thomas, S Jiang - Scientific reports, 2021 - nature.com
Nuclear magnetic resonance spectroscopy (MRS) allows for the determination of atomic
structures and concentrations of different chemicals in a biochemical sample of interest …

Hypercomplex low rank reconstruction for nmr spectroscopy

Y Guo, J Zhan, Z Tu, Y Zhou, J Wu, Q Hong, Y Huang… - Signal Processing, 2023 - Elsevier
Nuclear magnetic resonance (NMR) spectroscopy serves as an important tool to analyze
chemicals and proteins in bioengineering. Multi-dimensional NMR offers a major …

[HTML][HTML] A hybrid denoising method for low-field nuclear magnetic resonance data

Y Zhao, R Xie, K Huang, H Su, J Guo - Magnetic Resonance Letters, 2024 - Elsevier
Low-field nuclear magnetic resonance (NMR) has broad application prospects in the
exploration and development of unconventional oil and gas reservoirs. However, NMR …

Stationary wavelet denoising of solid-state NMR spectra using multiple similar measurements

P Song, J Xu, X Liu, Z Zhang, X Rao… - Journal of Magnetic …, 2024 - Elsevier
Accumulating several scans of free induction decays is always needed to improve the signal-
to-noise ratio of NMR spectra, especially for the low gyromagnetic ratio solid-state NMR. In …

GRIN-toolbox: A versatile and light toolbox for NMR inversion

B Chen, L Wu, Y Chen, Z Fang, Y Huang… - Journal of Magnetic …, 2023 - Elsevier
NMR technique serves as a powerful analytical tool with diverse applications in fields such
as chemistry, biology, and material science. However, the effectiveness of NMR heavily …