A language-driven Mamba framework for low-dose CT denoising uses a frozen vision-language model to provide semantic supervision, achieving marginal but consistent quantitative gains over previous methods.
Self-adaptive weight embedded lightweight network using semi- supervised learning for low-dose CT image denoising,
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LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models
A language-driven Mamba framework for low-dose CT denoising uses a frozen vision-language model to provide semantic supervision, achieving marginal but consistent quantitative gains over previous methods.