UniPET proposes a universal PET denoising network with style alignment network (SAN) and region-aware learning strategy (RALS) to handle varied dose reduction factors via domain generalization.
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2026 2verdicts
UNVERDICTED 2representative citing papers
A training-free global-local skipping strategy accelerates 3D diffusion-based PET denoising by over an order of magnitude while maintaining or improving image quality across multiple tracers.
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UniPET: a universal network for high-quality PET image denoising across varied dose reduction factors
UniPET proposes a universal PET denoising network with style alignment network (SAN) and region-aware learning strategy (RALS) to handle varied dose reduction factors via domain generalization.
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Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction
A training-free global-local skipping strategy accelerates 3D diffusion-based PET denoising by over an order of magnitude while maintaining or improving image quality across multiple tracers.