Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI. (arXiv:2207.02390v1 [cs.CV])

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. Nevertheless, due to the complexity of the Transformer, the
application of fast MRI may not be straightforward. The main obstacle is the
computational cost of …

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