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InfoResearchPeer-reviewed
C-GAN: Medical Image Steganography Based on Convergent GANs With Localization
- Published
- Record updated
Summary
Researchers propose C-GAN, a medical image steganography method that hides diagnostic reports inside cover images using a generator, extractor and discriminator trained end-to-end. The method adds a Zero-centered Wasserstein distance for stable training and local regularization on the generator to raise embedding capacity. Experiments on the Open-I, LGK and COV-CTR medical datasets report better capacity, detectability and convergence rate than recent state-of-the-art methods.