A novel zero-watermarking scheme with enhanced distinguishability and robustness for volumetric medical imaging

Abstract The authenticity and copyright protection of volumetric medical images has become extremely important when these images are distributed online for diagnosis and education purpose. Compared to the authenticity and copyright protection of conventional images, there are two additional challenges for protecting the volumetric medical images. On one hand, the content of the protected medical images must be distortion-free to ensure unbiased diagnosis. On the other hand, it requires enhanced distinguishability to avoid misclassification of non-protected images into the protected set because volumetric medical images of different persons in the same modality share similar visual structures. To address these issues, a novel multi-slice feature based zero-watermarking scheme with enhanced distinguishability and robustness for volumetric medical imaging is proposed. In this scheme, ring statistics are deployed to guarantee both the watermarking distinguishability and robustness. In addition, an intra-slice variation based mechanism is designed to further enhance the watermarking distinguishability. Finally, a logistic-logistic system based chaotic map is used to ensure the watermarking security. Our experimental results demonstrate that the proposed scheme not only satisfies the lossless quality requirement but also ensures the watermarking distinguishability and robustness, which outperforms the state-of-the-art schemes.