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Photon-counting CT using a Conditional Diffusion Model for Super-resolution and Texture-preservation
Ultra-high resolution images are desirable in photon counting CT (PCCT), but resolution is physically limited by interactions such as charge sharing.
A hierarchical approach to deep learning and its application to tomographic reconstruction
Here we present a novel framework to solve such problems with deep learning by casting the original problem as a continuum of intermediate representations between the input and output data.
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