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eess.IV2024★ 1 cited
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning
Shanshan Wang, Ruoyou Wu, Sen Jia +4
Deep learning (DL) has emerged as a leading approach in accelerating MR imaging. It employs deep neural networks to extract knowledge from available datasets and then applies the t…
eess.IV2022★ 95 cited
High-Frequency Space Diffusion Models for Accelerated MRI
Chentao Cao, Zhuo-Xu Cui, Yue Wang +5
Diffusion models with continuous stochastic differential equations (SDEs) have shown superior performances in image generation. It can serve as a deep generative prior to solving t…