Deep learning reconstruction allows low-dose imaging while maintaining image quality: comparison of deep learning reconstruction and hybrid iterative reconstruction in contrast-enhanced abdominal CT.

Tamura, Akio; Mukaida, Eisuke; Ota, Yoshitaka; Nakamura, Iku; Arakita, Kazumasa; Yoshioka, Kunihiro

Tamura, Akio; Mukaida, Eisuke; Ota, Yoshitaka; Nakamura, Iku; Arakita, Kazumasa; Yoshioka, Kunihiro.

Afiliação

Tamura A; Department of Radiology, Iwate Medical University School of Medicine, Iwate, Japan.
Mukaida E; Department of Radiology, Iwate Medical University School of Medicine, Iwate, Japan.
Ota Y; Division of Central Radiology, Iwate Medical University Hospital, Iwate, Japan.
Nakamura I; Iwate Medical University School of Medicine, Iwate, Japan.
Arakita K; Healthcare IT Development Center, Canon Medical Systems Corporation, Otawara, Japan.
Yoshioka K; Department of Radiology, Iwate Medical University School of Medicine, Iwate, Japan.

Quant Imaging Med Surg ; 12(5): 2977-2984, 2022 May.

Article em En | MEDLINE | ID: mdl-35502368

Palavras-chave

Computed tomography (CT); advanced intelligent clear-IQ engine (AiCE); contrast-to-noise ratio (CNR); deep learning reconstruction (DLR); noise reduction

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Observational_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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