Presentation Details
SMIR: A Transformer-Based Model for MRI super-resolution reconstruction
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Updated Time：2021-10-30 22:03:44 Hits：2033
Poster Presentation
Start Time：2021-11-13 09:20（Asia/Shanghai）
Duration：5min
Session：Pos Poster »
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Abstract
Down-sampling magnetic resonance imaging super-resolution reconstruction is one of the main problems in the field of accelerating magnetic resonance imaging research. The current method with better results is the traditional method of compressed sensing, but the solution requires iteration, which consumes a lot of time and only solves the reconstruction for a single image. At present, the more advanced image restoration methods are based on convolutional neural networks, but few people have tried to apply Transformer to the field of medical image reconstruction and have shown relatively good results. In this article, we propose a magnetic resonance imaging reconstruction model SMIR based on Swin Transformers, namely SMIR. SMIR consists of two modules: a multi-level feature extraction module and a reconstruction module. The model combines frequency domain and spatial domain losses to better reconstruct image details. We compared this model with some traditional image processing methods and advanced convolutional neural networks image restoration methods. The experimental results show that our method achieves the best results.
Keywords
Transformers,Magnetic resonance imaging (MRI),Deep learning,Super-resolution Reconstruction
Speaker
超 严
无 北京理工大学Submission Author
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Important Date
-
Conference Date
Nov 13
2021
toNov 14
2021
-
Sep 30 2021
Contribution Submission Deadline
-
Nov 14 2021
Registration deadline
Sponsored By
Medical Physics Branch of Chinese Society of Biomedical Engineering
IEEE Beijing Section
Life Electronics Society of Chinese Institute of Electronics
IEEE Beijing Section
Life Electronics Society of Chinese Institute of Electronics
Organized By
Anhui Biomedical Engineering Society.
University of Science and Technology of China
University of Science and Technology of China
Contact Information
- Mrs. Yang
- ic******@ustc.edu.cn
- +86********
Previous Conferences
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2017-11-04 China Beijing,China
2017 International Conference on Medical Imaging Physics and Engineering -
2017-11-03 China 海淀区
2017 IEEE 国际医学影像物理和工程大会 -
2013-10-19 China 沈阳市
2013 IEEE International Conference on Medical Imaging Physics and Engineering (ICMIPE)
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