Computed Tomography slice interpolation in the longitudinal direction based on deep learning techniques: To reduce slice thickness or slice increment without dose increase.

Wu, Shuqiong; Nakao, Megumi; Imanishi, Keiho; Nakamura, Mitsuhiro; Mizowaki, Takashi; Matsuda, Tetsuya

Wu, Shuqiong; Nakao, Megumi; Imanishi, Keiho; Nakamura, Mitsuhiro; Mizowaki, Takashi; Matsuda, Tetsuya.

Afiliação

Wu S; The Institute of Scientific and Industrial Research, Osaka University, Ibaraki, Osaka, Japan.
Nakao M; Graduate School of Informatics, Kyoto University, Kyoto, Japan.
Imanishi K; e-Growth Co., Ltd., Kyoto, Japan.
Nakamura M; Division of Medical Physics, Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Mizowaki T; Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Matsuda T; Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

PLoS One ; 17(12): e0279005, 2022.

Article em En | MEDLINE | ID: mdl-36520814

Assuntos

Aprendizado Profundo; Humanos; Processamento de Imagem Assistida por Computador/métodos; Tomografia Computadorizada por Raios X/métodos; Artefatos; Algoritmos

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Idioma: En Ano de publicação: 2022 Tipo de documento: Article