An Attention-Based, Dual-Domain Adaptive Convolutional Neural Network for Fast MRI Reconstruction-Reference-Cited by-同舟云学术

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An Attention-Based, Dual-Domain Adaptive Convolutional Neural Network for Fast MRI Reconstruction

Published:2024-04-26 Issue: Volume:33 Page:242-249
ISSN:
Container-title:Proceedings of the 2024 10th International Conference on Computing and Artificial Intelligence
language:
Short-container-title:

Author:

Hu Rui¹^ORCID,Chen Shufan²^ORCID,Tao Jinxu¹^ORCID

Affiliation:

1. Department of Electronic Engineering and Information Science, University of Science and Technology of China, China

2. Department of Automation, University of Science and Technology of China, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3669754.3669790

Reference28 articles.

1. MRI banding removal via adversarial training;Defazio Aaron;Advances in Neural Information Processing Systems,2020

2. Compressed sensing

3. Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020).

4. Tianming Du, Honggang Zhang, Yuemeng Li, Stephen Pickup, Mark Rosen, Rong Zhou, Hee Kwon Song, and Yong Fan. 2021. Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation. Medical image analysis 72 (2021), 102098.

5. Taejoon Eo, Yohan Jun, Taeseong Kim, Jinseong Jang, Ho-Joon Lee, and Dosik Hwang. 2018. KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images. Magnetic resonance in medicine 80, 5 (2018), 2188–2201.

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