Ring artifact removal for differential phase-contrast X-ray computed tomography using a conditional generative adversarial network.

Huang, Zhuoran; Sunaguchi, Naoki; Shimao, Daisuke; Enomoto, Atsushi; Ichihara, Shu; Yuasa, Tetsuya; Ando, Masami

Huang, Zhuoran; Sunaguchi, Naoki; Shimao, Daisuke; Enomoto, Atsushi; Ichihara, Shu; Yuasa, Tetsuya; Ando, Masami.

Afiliação

Huang Z; Department of Radiological and Medical Laboratory Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan.
Sunaguchi N; Department of Radiological and Medical Laboratory Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan. sunaguchi@met.nagoya-u.ac.jp.
Shimao D; Department of Radiological Technology, Hokkaido University of Science, Sapporo, Japan.
Enomoto A; Department of Pathology, Graduate School of Medicine, Nagoya University, Nagoya, Japan.
Ichihara S; Department of Pathology, Nagoya Medical Center, Nagoya, Japan.
Yuasa T; Graduate School of Engineering and Science, Yamagata University, Yonezawa, Japan.
Ando M; High Energy Accelerator Research Organization, Tsukuba, Japan.

Int J Comput Assist Radiol Surg ; 16(11): 1889-1900, 2021 Nov.

Article em En | MEDLINE | ID: mdl-34652605

Assuntos

Artefatos; Tomografia Computadorizada por Raios X; Humanos; Processamento de Imagem Assistida por Computador; Imagens de Fantasmas

Palavras-chave

Generative adversarial network; Machine learning; Phase-contrast X-ray CT; Ring artifact; X-ray dark-field imaging

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tomografia Computadorizada por Raios X / Artefatos Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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