Correction of motion artifact in CL based on MAFusNet.

Jia, Tong; Shi, Liu; Wei, Cunfeng; Shi, Rongjian; Liu, Baodong

Jia, Tong; Shi, Liu; Wei, Cunfeng; Shi, Rongjian; Liu, Baodong.

Afiliación

Jia T; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
Shi L; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China.
Wei C; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
Shi R; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China.
Liu B; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.

J Xray Sci Technol ; 31(2): 393-407, 2023.

Article en En | MEDLINE | ID: mdl-36710712

Palabras clave

Computed laminography; deep learning; image deblurring; rotational motion blur

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Xray Sci Technol Asunto de la revista: RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

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