Medical Imaging 2024: Physics of Medical Imaging 2024
DOI: 10.1117/12.3007693
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Diffusion posterior sampling for nonlinear CT reconstruction

Shudong Li,
Matthew Tivnan,
Joseph W. Stayman

Abstract: 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 low-quality measurements. This technique is attractive since it permits a one-time, unsupervised training of a CT prior; which can then be incorporated with an arbitrary data model. However, current methods only rely … Show more

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