Diffusion Posterior Sampling for Nonlinear CT Reconstruction
Diffusion models have been demonstrated as powerful deep learning tools for image generation in CT reconstruction and restoration. Recently, diffusion posterior sampling, where a score-based diffusion prior is combined with a likelihood model, has been used to produce high quality CT images given lo...
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Published in | Proceedings of SPIE, the international society for optical engineering Vol. 12925 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
01.02.2024
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Online Access | Get more information |
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