Application of a Deep Learning Algorithm for Combined Super-Resolution and Partial Fourier Reconstruction Including Time Reduction in T1-Weighted Precontrast and Postcontrast Gradient Echo Imaging of Abdominopelvic MR Imaging

Purpose: The purpose of this study was to test the technical feasibility and the impact on the image quality of a deep learning-based super-resolution reconstruction algorithm in 1.5 T abdominopelvic MR imaging. Methods: 44 patients who underwent abdominopelvic MRI were retrospectively included, of...

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Detalles Bibliográficos
Autores principales: Wessling, Daniel, Herrmann, Judith, Afat, Saif, Nickel, Dominik, Almansour, Haidara, Keller, Gabriel, Othman, Ahmed E., Brendlin, Andreas S., Gassenmaier, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600324/
https://www.ncbi.nlm.nih.gov/pubmed/36292057
http://dx.doi.org/10.3390/diagnostics12102370

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600324/
https://www.ncbi.nlm.nih.gov/pubmed/36292057
http://dx.doi.org/10.3390/diagnostics12102370

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