Unsupervised Denoising of Real Clinical Low Dose Liver CT with Perceptual Attention Networks

In three linesPaper presents unsupervised denoising framework for low-dose liver CT using Cycle-GAN-inspired approach. Combines U-Net, attention mechanisms, residual networks with perceptual loss. Validated on real clinical dataset with radiologist evaluation.

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