A robust tensor watermarking algorithm for diffusion-tensor images  

作　　者：Chengmeng LIU Zhi LI Guomei WANG Long ZHENG 

机构地区：[1]State Key Laboratory of Public Big Data,College of Computer Science and Technology,Guizhou University,Guiyang 550025,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2024年第3期384-397,共14页信息与电子工程前沿（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(No.62062023);the Guizhou Science and Technology Plan Project of China(No.ZK[2021]-YB314);the Stadholder Foundation of Guizhou Province,China(No.2007(14))。

摘　　要：Watermarking algorithms that use convolution neural networks have exhibited good robustness in studies of deep learning networks.However,after embedding watermark signals by convolution,the feature fusion eficiency of convolution is relatively low;this can easily lead to distortion in the embedded image.When distortion occurs in medical images,especially in diffusion tensor images(DTIs),the clinical value of the DTI is lost.To address this issue,a robust watermarking algorithm for DTIs implemented by fusing convolution with a Transformer is proposed to ensure the robustness of the watermark and the consistency of sampling distance,which enhances the quality of the reconstructed image of the watermarked DTIs after embedding the watermark signals.In the watermark-embedding network,Ti-weighted(Tlw)images are used as prior knowledge.The correlation between T1w images and the original DTI is proposed to calculate the most significant features from the T1w images by using the Transformer mechanism.The maximum of the correlation is used as the most significant feature weight to improve the quality of the reconstructed DTI.In the watermark extraction network,the most significant watermark features from the watermarked DTI are adequately learned by the Transformer to robustly extract the watermark signals from the watermark features.Experimental results show that the average peak signal-to-noise ratio of the watermarked DTI reaches 50.47 dB,the diffusion characteristics such as mean diffusivity and fractional anisotropy remain unchanged,and the main axis deflection angleαAc is close to 1.Our proposed algorithm can effectively protect the copyright of the DTI and barely affects the clinical diagnosis.

关 键 词：Robust watermarking algorithm Transformer Image reconstruction Diffusion tensor images Soft attention Hard attention Tl-weighted images 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]