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.

Data and Resources

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

DOI retrieved: December 16, 2024

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