The application of sparse-sampling techniques to NMR data acquisition would benefit from reliable quality measurements for reconstructed spectra. We introduce a pair of noise-normalized measurements, and , for differentiating inadequate modelling from overfitting. While and can be used jointly for methods that do not enforce exact agreement between the back-calculated time domain and the original sparse data, the cross-validation measure is applicable to all reconstruction algorithms. We show that the fidelity of reconstruction is sensitive to changes in and that model overfitting results in elevated and reduced spectral quality
Although the discrete Fourier transform played an enabling role in the development of modern NMR spe...
Non-uniform weighted sampling (NUWS) is a sampling strategy, related to non-uniform sampling (NUS) i...
Nuclear magnetic resonance spectroscopy is a powerful biophysical technique for characterizing biolo...
In this paper we propose a novel method for magnetic resonance spectroscopy (MRS) fitting quality as...
The need to reduce data acquisition times of multidimensional NMR experiments has fostered considera...
Nonuniform sampling (NUS) of multidimensional NMR data offers significant time savings while improvi...
Low spectral resolution and extensive peak overlap are the common challenges that preclude quantitat...
The time required to complete a multidimensional NMR experiment is directly proportional to the numb...
Low spectral resolution and extensive peak overlap are the common challenges that preclude quantitat...
In this thesis, signal sampling and processing techniques are developed for magnetic resonance appli...
OBJECTIVES: The aim of this study was to investigate the influence of variable density and data-driv...
The discovery of the theory of compressed sensing brought the realisation that many inverse problems...
Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain ...
The discovery of the theory of compressed sensing brought the realisation that many inverse problems...
We discuss Nuclear Magnetic Resonance (NMR) signal detection in unstable magnetic field B and low S...
Although the discrete Fourier transform played an enabling role in the development of modern NMR spe...
Non-uniform weighted sampling (NUWS) is a sampling strategy, related to non-uniform sampling (NUS) i...
Nuclear magnetic resonance spectroscopy is a powerful biophysical technique for characterizing biolo...
In this paper we propose a novel method for magnetic resonance spectroscopy (MRS) fitting quality as...
The need to reduce data acquisition times of multidimensional NMR experiments has fostered considera...
Nonuniform sampling (NUS) of multidimensional NMR data offers significant time savings while improvi...
Low spectral resolution and extensive peak overlap are the common challenges that preclude quantitat...
The time required to complete a multidimensional NMR experiment is directly proportional to the numb...
Low spectral resolution and extensive peak overlap are the common challenges that preclude quantitat...
In this thesis, signal sampling and processing techniques are developed for magnetic resonance appli...
OBJECTIVES: The aim of this study was to investigate the influence of variable density and data-driv...
The discovery of the theory of compressed sensing brought the realisation that many inverse problems...
Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain ...
The discovery of the theory of compressed sensing brought the realisation that many inverse problems...
We discuss Nuclear Magnetic Resonance (NMR) signal detection in unstable magnetic field B and low S...
Although the discrete Fourier transform played an enabling role in the development of modern NMR spe...
Non-uniform weighted sampling (NUWS) is a sampling strategy, related to non-uniform sampling (NUS) i...
Nuclear magnetic resonance spectroscopy is a powerful biophysical technique for characterizing biolo...