Filter2Noise: A Framework for Interpretable and Zero-Shot Low-Dose CT Image Denoising

arXiv:2504.13519v2 Announce Type: replace-cross Abstract: Noise in low-dose computed tomography (LDCT) can obscure important diagnostic details. While deep learning offers powerful denoising, supervised methods require impractical paired data, and self-supervised alternatives ...

🔗 Read more: https://arxiv.org/abs/2504.13519

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