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ROI-based fragile medical image watermarking technique for tamper detection and recovery using variance

机译：基于ROI的易碎医学图像水印技术，用于使用方差进行篡改检测和恢复

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摘要

Protection of medical images using watermarking is an imperative area of research. In telemedicine, medical images are exchanged between distant places through unsecure networks like internet for diagnosis purpose. During this transfer, medical images may be tampered intentionally or accidentally. The medical practitioner has to check the integrity of Region of Interest (ROI) in the received medical image before making any diagnostic decisions. In this paper, we are developing a novel fragile and block based medical image watermarking technique for producing high quality watermarked medical images, verifying the integrity of ROI, detecting accurately the tampered blocks inside ROI using both average and variance of blocks and recovering the original ROI with zero loss. In the proposed method, the medical image is segmented into three sets of pixels: ROI pixels, Region of Non Interest (RONI) pixels and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on number of medical images reveal that proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI of watermarked medical images with 100% accuracy and recovers the original ROI without any loss.
机译：使用水印保护医学图像是当务之急。在远程医疗中，医学图像是通过不安全的网络（例如互联网）在远处之间交换以进行诊断的。在此传输过程中，医学图像可能被有意或无意地篡改。在做出任何诊断决定之前，医生必须检查接收到的医学图像中感兴趣区域（ROI）的完整性。在本文中，我们正在开发一种新颖的基于脆弱和基于块的医学图像水印技术，以产生高质量的带水印的医学图像，验证ROI的完整性，使用块的平均值和方差来准确检测ROI内部被篡改的块并恢复原始ROI零损失。在提出的方法中，医学图像被分成三组像素：ROI像素，非关注区域（RONI）像素和边界像素。然后，将认证数据和ROI信息嵌入边界像素中。 ROI的恢复数据已嵌入到RONI中。在许多医学图像上进行的实验结果表明，该方法可生成高质量的水印医学图像，以100％的精度识别水印医学图像ROI内部是否存在篡改，并且可以无损失地恢复原始ROI。

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