NMR spectrum reconstruction as a pattern recognition problem.
CNN
DNN
Non-uniform sampling
Nuclear magnetic resonance
Wave-net
Journal
Journal of magnetic resonance (San Diego, Calif. : 1997)
ISSN: 1096-0856
Titre abrégé: J Magn Reson
Pays: United States
ID NLM: 9707935
Informations de publication
Date de publication:
01 2023
01 2023
Historique:
received:
13
09
2022
revised:
15
11
2022
accepted:
19
11
2022
pubmed:
3
12
2022
medline:
24
1
2023
entrez:
2
12
2022
Statut:
ppublish
Résumé
A new deep neural network based on the WaveNet architecture (WNN) is presented, which is designed to grasp specific patterns in the NMR spectra. When trained at a fixed non-uniform sampling (NUS) schedule, the WNN benefits from pattern recognition of the corresponding point spread function (PSF) pattern produced by each spectral peak resulting in the highest quality and robust reconstruction of the NUS spectra as demonstrated in simulations and exemplified in this work on 2D
Identifiants
pubmed: 36459916
pii: S1090-7807(22)00200-2
doi: 10.1016/j.jmr.2022.107342
pii:
doi:
Substances chimiques
Ubiquitin
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
107342Subventions
Organisme : NIGMS NIH HHS
ID : P41 GM111135
Pays : United States
Informations de copyright
Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.