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Found 2 papers, 1 papers with code
PET image denoising based on denoising diffusion probabilistic models
Regional and surface quantification shows that employing MR prior as the network input while embedding PET image as a data-consistency constraint during inference can achieve the best performance.
Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image Denoising
In this work, we proposed an efficient spatial and channel-wise encoder-decoder transformer, Spach Transformer, that can leverage spatial and channel information based on local and global MSAs.
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