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    • HRDRL-Net: a deep reinforcement learning framework for high-resolution reconstruction of low-dose computed tomography images

    • Vol. 31, Issue 10, Pages: 3779-3801(2026)   

      Received:21 October 2025,

      Revised:2026-03-02,

      Accepted:09 March 2026,

      Published:16 October 2026

    • DOI: 10.11834/jig.250502     

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  • Zhang Shengnan, Sun Zheng, Yu Han, Gao Zhangshuo, Ding Gang’ao. 2026. HRDRL-Net: a deep reinforcement learning framework for high-resolution reconstruction of low-dose computed tomography images. Journal of Image and Graphics, 31(10):3779-3801 DOI: 10.11834/jig.250502.
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相关作者

ZHANG Shengnan 华北电力大学 电子与通信工程系
SUN Zheng 华北电力大学 电子与通信工程系;华北电力大学 河北省电力物联网技术重点实验室
DING Gangao 华北电力大学 电子与通信工程系
Ai Bing 华北电力大学电子与通信工程系
Hou Yingsa 华北电力大学电子与通信工程系
Sun Meichen 华北电力大学电子与通信工程系
Changde Du 中国科学院自动化研究所脑图谱与类脑智能研究中心;中国科学院自动化研究所多模态人工智能系统全国重点实验室
Qiongyi Zhou 中国科学院自动化研究所脑图谱与类脑智能研究中心;中国科学院大学人工智能学院

相关机构

Research Center for Brain Mapping and Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences
School of Artificial Intelligence, University of Chinese Academy of Sciences
School of Communication and Information Engineering, Shanghai University
Paul C Lauterbur Research Center, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
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