title: Unbiased measurements of reconstruction fidelity of sparsely sampled magnetic resonance spectra.
abstract: 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.
authors.affiliation: Department of Biochemistry, Duke University Medical Center, Durham, North Carolina 27710, USA.
authors.forename: Qinglin
authors.initials: Q
authors.lastname: Wu
authors.affiliation: Department of Biochemistry, Duke University Medical Center, Durham, North Carolina 27710, USA.
authors.forename: Brian E
authors.initials: BE
authors.lastname: Coggins
authors.affiliation: Department of Biochemistry, Duke University Medical Center, Durham, North Carolina 27710, USA.
authors.forename: Pei
authors.identifier: 0000-0002-7823-3416
authors.initials: P
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D015982:Bias; D019277:Entropy; D007091:Image Processing, Computer-Assisted; D009682:Magnetic Resonance Spectroscopy