AI RESEARCH
Progressive $\mathcal{J}$-Invariant Self-supervised Learning for Low-Dose CT Denoising
arXiv CS.CV
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ArXi:2601.14180v3 Announce Type: replace Self-supervised learning has been increasingly investigated for low-dose computed tomography (LDCT) image denoising, as it alleviates the dependence on paired normal-dose CT (NDCT) data, which are often difficult to collect. However, many existing self-supervised blind-spot denoising methods suffer from