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Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI

Fast MRI aims to reconstruct a high fidelity image from partially observed measurements. Exuberant development in fast MRI using deep learning has been witnessed recently. Meanwhile, novel deep learning paradigms, e.g., Transformer based models, are fast-growing in natural language processing and promptly developed for computer vision and medical image analysis due to their prominent performance.

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Cite this as

Jiahao Huang, Xiaodan Xing, Zhifan Gao, Guang Yang (2024). Dataset: Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI. https://doi.org/10.57702/qme2glxb

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Additional Info

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Created December 16, 2024
Last update December 16, 2024
Author Jiahao Huang
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Xiaodan Xing
Zhifan Gao
Guang Yang
Homepage https://github.com/ayanglab/SDAUT