Low-Dose Pet Image Restoration With 2D And 3D Network Prior Learning

机译：通过2D和3D网络事前学习进行低剂量宠物图像恢复

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Reducing the dose of positron emission tomography (PET) imaging is a hot research area for avoiding too much radiation exposure. However, low-dose imaging faces the challenges of different degradation factors such as noise and artifacts. To restore high-q

机译：减少正电子发射断层扫描（PET）成像的剂量是一种热门研究区域，用于避免过多的辐射曝光。然而，低剂量成像面临着不同劣化因子的挑战，例如噪声和伪影。恢复高Q

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《International Symposium on Biomedical Imaging Workshops》|2020年|1-4|共4页
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Yu Gong; Hongming Shan; Yueyang Teng; Hairong Zheng; Ge Wang; Shanshan Wang;
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Deep learning; normal-dose PET restoration; WGAN;

机译：深度学习;常规剂量PET修复; WGAN;

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专利

1. Correction for “3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2D Trained Network” [J] . Hongming Shan, Yi Zhang, Qingsong Yang, IEEE Transactions on Medical Imaging . 2018,第12期

机译：对“通过来自2D训练网络的转移学习进行低剂量CT的3D卷积编码器/解码器网络”的更正
2. Semi-Supervised Learning for Low-Dose CT Image Restoration Using Generative Adversarial Networks (GANs) [J] . Choi K., Kim S. W. Medical Physics . 2018,第6期

机译：使用生成对策网络（GANS）的低剂量CT图像恢复半监督学习
3. Blind Image Restoration for Low-Dose Lung CT Using Residual Network and Transfer Learning [J] . Zhong A., Li B., Luo N., Medical Physics . 2019,第6期

机译：使用剩余网络和转移学习的低剂量肺CT盲图像恢复
4. Deeply-Supervised Multi-Dose Prior Learning For Low-Dose Pet Imaging [C] . Yu Gong, Hongming Shan, Yueyang Teng, International Symposium on Biomedical Imaging Workshops . 2020

机译：深度指导的多剂量先验学习，用于低剂量宠物成像
5. Learning 3D Model from 2D In-the-Wild Images [D] . Tran, Luan Quoc. 2020

机译：从野外图像的2D学习3D模型
6. 3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network [O] . Hongming Shan, Yi Zhang, Qingsong Yang, -1

机译：通过从2D训练有素的网络进行转移学习获得用于低剂量CT的3D卷积编码器/解码器网络
7. Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and Image-to-Image Translation from Unpaired Supervision [O] . Tung, Hsiao-Yu Fish, Harley, Adam W., Seto, William, 2017

机译：对抗逆向图形网络：学习2D到3D提升和不成对监督的图像到图像翻译

Low-Dose Pet Image Restoration With 2D And 3D Network Prior Learning

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