Work

Unbiased measurements of reconstruction fidelity of sparsely sampled magnetic resonance spectra

Year: 2016

Type: article

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, "Equation missing" and "Equation missing", for differentiating inadequate modelling from overfitting. While "Equation missing" and "Equation missing" 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 "Equation missing" is applicable to all reconstruction algorithms. We show that the fidelity of reconstruction is sensitive to changes in "Equation missing" and that model overfitting results in elevated "Equation missing" and reduced spectral quality.

Source: Nature Communications

DOI: 10.1038/ncomms12281

Authors: Qinglin Wu, Brian E. Coggins, Pei Zhou

Institution: Duke Medical Center

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: gold

Estimated APC paid: $6,990

Funders: National Institutes of Health, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases