C-GAN: Medical Image Steganography Based on Convergent GANs With Localization

This paper presents C-GAN, a method for medical image steganography (hiding secret messages inside medical images in a way that is undetectable to observers) using GANs (generative adversarial networks, a type of AI system where two neural networks compete to improve each other). The researchers improved previous steganography approaches by using a special measurement called Zero-centered Wasserstein distance to make training more stable and by adding local regularization to increase how much data can be hidden while keeping images looking natural.