A generalized image quality improvement strategy of cone-beam CT using multiple spectral CT labels in Pix2pix GAN

Yangkang Jiang Zhejiang University Yibao Zhang Shenzhen Bay Laboratory Chen Luo Peking University Cancer Hospital & Institute Pengfei Yang Zhejiang University Jing Wang Zhejiang University Xiaokun Liang Chinese Academy of Sciences Wei Zhao Beihang University Ren-Cang Li The University of Texas at Arlington Tianye Niu Shenzhen Bay Laboratory

Machine Learning mathscidoc:2309.41004

Physics in Medicine & Biology, 67, 115003, 2022.8
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deep learning, multiple spectral cone-beam CT, Pix2pix GAN, scatter correction
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@inproceedings{yangkang2022a,
  title={A generalized image quality improvement strategy of cone-beam CT using multiple spectral CT labels in Pix2pix GAN},
  author={Yangkang Jiang, Yibao Zhang, Chen Luo, Pengfei Yang, Jing Wang, Xiaokun Liang, Wei Zhao, Ren-Cang Li, and Tianye Niu},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20230925012611093465761},
  booktitle={Physics in Medicine & Biology},
  volume={67},
  pages={115003},
  year={2022},
}
Yangkang Jiang, Yibao Zhang, Chen Luo, Pengfei Yang, Jing Wang, Xiaokun Liang, Wei Zhao, Ren-Cang Li, and Tianye Niu. A generalized image quality improvement strategy of cone-beam CT using multiple spectral CT labels in Pix2pix GAN. 2022. Vol. 67. In Physics in Medicine & Biology. pp.115003. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20230925012611093465761.
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