Model‐informed unsupervised deep learning approaches to frequency and phase correction of MRS signals

PURPOSE: A supervised deep learning (DL) approach for frequency and phase correction (FPC) of MRS data recently showed encouraging results, but obtaining transients with labels for supervised learning is challenging. This work investigates the feasibility and efficiency of unsupervised deep learning...

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Detalles Bibliográficos
Autores principales: Shamaei, Amirmohammad, Starcukova, Jana, Pavlova, Iveta, Starcuk, Zenon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Research Articles—Computer Processing and Modeling
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098589/
https://www.ncbi.nlm.nih.gov/pubmed/36367249
http://dx.doi.org/10.1002/mrm.29498

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098589/
https://www.ncbi.nlm.nih.gov/pubmed/36367249
http://dx.doi.org/10.1002/mrm.29498

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