Super-Resolution Reconstruction of 3T-Like Images From 0.35T MRI Using a Hybrid Attention Residual Network-Reference-Cited by-同舟云学术

Super-Resolution Reconstruction of 3T-Like Images From 0.35T MRI Using a Hybrid Attention Residual Network

Author:

Jiang Jialiang¹,Qi Fulang¹,Du Huiyu¹,Xu Jianan¹,Zhou Yufu¹,Gao Dayong²,Qiu Bensheng¹^ORCID

Affiliation:

1. Center for Biomedical Imaging, University of Science and Technology of China, Hefei, China

2. Department of Mechanical Engineering, University of Washington, Seattle, WA, USA

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

Reference28 articles.

Cited by 6 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. An Attention-Based, Dual-Domain Adaptive Convolutional Neural Network for Fast MRI Reconstruction;Proceedings of the 2024 10th International Conference on Computing and Artificial Intelligence;2024-04-26

3. Residual Attention Mechanism-Based MRI Super-Resolution;2024 4th International Conference on Neural Networks, Information and Communication (NNICE);2024-01-19

5. CSA: A Channel-Separated Attention Module for Enhancing MRI Reconstruction;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24