Image quality improvement with deep learning‐based reconstruction on abdominal ultrahigh‐resolution CT: A phantom study

PURPOSE: In an ultrahigh‐resolution CT (U‐HRCT), deep learning‐based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation doses assuming an abdominal CT protocol. MET...

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Detalles Bibliográficos
Autores principales: Shirasaka, Takashi, Kojima, Tsukasa, Funama, Yoshinori, Sakai, Yuki, Kondo, Masatoshi, Mikayama, Ryoji, Hamasaki, Hiroshi, Kato, Toyoyuki, Ushijima, Yasuhiro, Asayama, Yoshiki, Nishie, Akihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292685/
https://www.ncbi.nlm.nih.gov/pubmed/34159736
http://dx.doi.org/10.1002/acm2.13318

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292685/
https://www.ncbi.nlm.nih.gov/pubmed/34159736
http://dx.doi.org/10.1002/acm2.13318

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