Patch-trained diffusion priors with shifted-grid patch inference match whole-image performance for MRI denoising and 2x super-resolution while using less memory.
In doing so, we seek to enable further study into the usage on patch-based methods in memory intensive inverse problems in higher resolution medical images
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Investigating the Feasibility of Patch-based Inference for Generalized Diffusion Priors in Inverse Problems for Medical Images
Patch-trained diffusion priors with shifted-grid patch inference match whole-image performance for MRI denoising and 2x super-resolution while using less memory.