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Unbiased measurements of reconstruction fidelity of sparsely sampled magnetic resonance spectra

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  • Qinglin Wu

    (Duke University Medical Center)

  • Brian E. Coggins

    (Duke University Medical Center)

  • Pei Zhou

    (Duke University Medical Center)

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.

Suggested Citation

  • Qinglin Wu & Brian E. Coggins & Pei Zhou, 2016. "Unbiased measurements of reconstruction fidelity of sparsely sampled magnetic resonance spectra," Nature Communications, Nature, vol. 7(1), pages 1-8, November.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12281
    DOI: 10.1038/ncomms12281
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