Hepatic vessel segmentation based on 3D swin-transformer with inductive biased multi-head self-attention.

Wu, Mian; Qian, Yinling; Liao, Xiangyun; Wang, Qiong; Heng, Pheng-Ann

Wu, Mian; Qian, Yinling; Liao, Xiangyun; Wang, Qiong; Heng, Pheng-Ann.

Afiliación

Wu M; Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Qian Y; Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Liao X; Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China. xiangyun-l@163.com.
Wang Q; Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Heng PA; Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.

BMC Med Imaging ; 23(1): 91, 2023 07 08.

Article en En | MEDLINE | ID: mdl-37422639

Asunto(s)

Cabeza; Hígado; Humanos; Hígado/diagnóstico por imagen; Atención; Procesamiento de Imagen Asistido por Computador/métodos

Palabras clave

3D swin transformer; Multi-head self-attention; Segmentation

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cabeza / Hígado Límite: Humans Idioma: En Revista: BMC Med Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

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