Impact of deep learning reconstruction on intracranial 1.5 T magnetic resonance angiography

PURPOSE: The purpose of this study was to evaluate whether deep learning reconstruction (DLR) improves the image quality of intracranial magnetic resonance angiography (MRA) at 1.5 T. MATERIALS AND METHODS: In this retrospective study, MRA images of 40 patients (21 males and 19 females; mean age, 65...

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Detalles Bibliográficos
Autores principales: Yasaka, Koichiro, Akai, Hiroyuki, Sugawara, Haruto, Tajima, Taku, Akahane, Masaaki, Yoshioka, Naoki, Kabasawa, Hiroyuki, Miyo, Rintaro, Ohtomo, Kuni, Abe, Osamu, Kiryu, Shigeru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068615/
https://www.ncbi.nlm.nih.gov/pubmed/34851499
http://dx.doi.org/10.1007/s11604-021-01225-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068615/
https://www.ncbi.nlm.nih.gov/pubmed/34851499
http://dx.doi.org/10.1007/s11604-021-01225-2

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