DIRECT-Net: A unified mutual-domain material decomposition network for quantitative dual-energy CT imaging.

Su, Ting; Sun, Xindong; Yang, Jiecheng; Mi, Donghua; Zhang, Yikun; Wu, Haodi; Fang, Shibo; Chen, Yang; Zheng, Hairong; Liang, Dong; Ge, Yongshuai

Su, Ting; Sun, Xindong; Yang, Jiecheng; Mi, Donghua; Zhang, Yikun; Wu, Haodi; Fang, Shibo; Chen, Yang; Zheng, Hairong; Liang, Dong; Ge, Yongshuai.

Afiliação

Su T; Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Sun X; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Yang J; Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Mi D; Department of Vascular Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Zhang Y; School of Computer Science and Engineering, Southeast University, Nanjing, China.
Wu H; Wuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology (HUST), Wuhan, China.
Fang S; Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Chen Y; School of Computer Science and Engineering, Southeast University, Nanjing, China.
Zheng H; Paul C Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Liang D; Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Ge Y; Paul C Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Med Phys ; 49(2): 917-934, 2022 Feb.

Article em En | MEDLINE | ID: mdl-34935146

Assuntos

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

Palavras-chave

CNN; deep learning; dual-energy CT; end-to-end; material decomposition; quantitative imaging

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Tomografia Computadorizada por Raios X Tipo de estudo: Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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