Model-based Deep Learning Reconstruction Using a Folded Image Training Strategy for Abdominal 3D T1-weighted Imaging

Purpose: To evaluate the feasibility of folded image training strategy (FITS) and the quality of images reconstructed using the improved model-based deep learning (iMoDL) network trained with FITS (FITS-iMoDL) for abdominal MR imaging. Methods: This retrospective study included abdominal 3D T1-weigh...

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Detalles Bibliográficos
Autores principales: Funayama, Satoshi, Motosugi, Utaroh, Ichikawa, Shintaro, Morisaka, Hiroyuki, Omiya, Yoshie, Onishi, Hiroshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society for Magnetic Resonance in Medicine 2022
Materias:
Major Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552667/
https://www.ncbi.nlm.nih.gov/pubmed/36351603
http://dx.doi.org/10.2463/mrms.mp.2021-0103

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552667/
https://www.ncbi.nlm.nih.gov/pubmed/36351603
http://dx.doi.org/10.2463/mrms.mp.2021-0103

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