Vol-Mark embeds watermarks into 3D medical volumes using contrastive learning for feature extraction and cubic difference expansion for embedding, achieving ACC above 0.90 against most attacks with reversible low-distortion properties.
Efficient robust reversible watermarking based on zms and integer wavelet transform
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Vol-Mark: A Watermark for 3D Medical Volume Data Via Cubic Difference Expansion and Contrastive Learning
Vol-Mark embeds watermarks into 3D medical volumes using contrastive learning for feature extraction and cubic difference expansion for embedding, achieving ACC above 0.90 against most attacks with reversible low-distortion properties.