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UniH3, a novel framework that Unifies Hierarchical Homogeneity and Heterogeneity and Heterogeneity for all-in-one medical image restoration, is proposed and extensive experiments on two large-scale benchmarks demonstrate that UniH3 achieves state-of-the-art performance on both all-in-one and single-task medical image restoration.
U-TTT adapts dynamically during inference, achieving state-of-the-art PET image denoising even under challenging distribution shifts.
