Variational mode decomposition for NMR echo data denoising

J Guo, R **e, Y Wang, L **ao, 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 …

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 …

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 …

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 …

Bioinformatic Analysis of Metabolomic Data: From Raw Spectra to Biological Insight

G Santamaria, FR Pinto - BioChem, 2024 - mdpi.com
Metabolites are at the end of the gene–transcript–protein–metabolism cascade. As such,
metabolomics is the omics approach that offers the most direct correlation with phenotype …

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 …

Mode Measurement of Vortex Electromagnetic Wave with Random Receiving Array Element Defects via Low Rank Matrix Completion

C He, Y Liao, C Ren - IEEE Transactions on Antennas and …, 2024 - ieeexplore.ieee.org
Vortex electromagnetic waves carrying orbital angular momentum have been widely studied
in many fields because of their unique helical phase structure. The vortex electromagnetic …

A generally regularized inversion for NMR applications and beyond

E Lin, B Chen, Z Ni, Y Huang, Y Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Nuclear magnetic resonance (NMR) technique presents a powerful analytical tool in the
fields of chemistry, biology, and material science. The performance of the NMR technique …

Magnetic resonance spectroscopy deep learning denoising using few in vivo data

D Chen, W Hu, H Liu, Y Zhou, T Qiu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Magnetic Resonance Spectroscopy (MRS) is a noninvasive tool to reveal metabolic
information. One challenge of 1 H-MRS is the low Signal-Noise Ratio (SNR). To improve the …