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Learning the degradation distribution for medical image superresolution via sparse swin transformer

  • Published:2023-08 Issue: Volume:114 Page:168-178
  • ISSN:0097-8493
  • Container-title:Computers & Graphics
  • language:en
  • Short-container-title:Computers & Graphics

Author:

Han XianjunORCID,Xie Zhaoyang,Chen Qianqian,Li XuejunORCID,Yang Hongyu

Funder

National Natural Science Foundation of China

Anhui Provincial Natural Science Foundation

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Human-Computer Interaction,General Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research into super-resolution in medical imaging from 2000 to 2023: bibliometric analysis and visualization;Quantitative Imaging in Medicine and Surgery;2024-07

2. Medical image super-resolution via transformer-based hierarchical encoder–decoder network;Network Modeling Analysis in Health Informatics and Bioinformatics;2024-06-24

3. Foreword special section on VSI: C&G VCBM 2022;Computers & Graphics;2024-04

4. Editorial Note Computers & Graphics Issue 114;Computers & Graphics;2023-08
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