Deep learning-driven multi-view multi-task image quality assessment method for chest CT image.

Su, Jialin; Li, Meifang; Lin, Yongping; Xiong, Liu; Yuan, Caixing; Zhou, Zhimin; Yan, Kunlong

Su, Jialin; Li, Meifang; Lin, Yongping; Xiong, Liu; Yuan, Caixing; Zhou, Zhimin; Yan, Kunlong.

Afiliación

Su J; School of Optoelectronic and Communication Engineering, Xiamen University of Technology, Xiamen, 361024, China.
Li M; Department of Medical Imaging, Affiliated Hospital of Putian University, Putian, 351100, China.
Lin Y; School of Clinical Medicine, Fujian Medical University, Fuzhou, 350122, China.
Xiong L; School of Optoelectronic and Communication Engineering, Xiamen University of Technology, Xiamen, 361024, China. yplin@t.xmut.edu.cn.
Yuan C; School of Optoelectronic and Communication Engineering, Xiamen University of Technology, Xiamen, 361024, China.
Zhou Z; Department of Medical Imaging, Affiliated Hospital of Putian University, Putian, 351100, China.
Yan K; Department of Medical Imaging, Affiliated Hospital of Putian University, Putian, 351100, China.

Biomed Eng Online ; 22(1): 117, 2023 Dec 06.

Article en En | MEDLINE | ID: mdl-38057850

Asunto(s)

Aprendizaje Profundo; Humanos; Estudios Retrospectivos; Tomografía Computarizada por Rayos X; Algoritmos; Procesamiento de Imagen Asistido por Computador/métodos

Palabras clave

Chest computed tomography images; Deep learning; Image quality assessment; Multi-task; Multi-view

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Aprendizaje Profundo Límite: Humans Idioma: En Revista: Biomed Eng Online Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2023 Tipo del documento: Article País de afiliación: China

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