E-healthcare requires communication of patient report to a specialized doctor in a real time scenario. Therefore, any harm to patient medical data can lead to a faulty diagnosis that can be lethal for the patient. To ensure safe and secure communication in E-healthcare framework, a high capacity dual image separable reversible data hiding algorithm in the encrypted domain has been presented in this paper. All compared reversible data hiding techniques have been shown predominant outcomes, yet just on natural images not on medical images because underflow problem may arise in medical images due to a large number of pixels have low-intensity values. Thus, an enhanced separable reversible data hiding technique in the encrypted domain has been introduced here that gives a higher embedding rate than all the looked at reversible data hiding techniques by embedding \(log_2(u-l+1)\) binary bits of patient information at non-seed pixels of the cover image without any occurrence of underflow and overflow problem so that empowering it to embed and recover information precisely from low-intensity pixels too. This property makes our proposed methodology truly reasonable for its utilization on medical images. For authentication analysis of electronic patient information (EPI) at the recipient end, a fragile watermark has also been embedded with EPI respectively. For all test images, embedding rate of 2.38 bits per pixel (bpp) with an average PSNR value is 41.05 dB is observed which demonstrates that the proposed method is capable of giving good quality stego images even at high payload also.

电子医疗保健需要在实时场景中将患者报告传达给专业医生。因此，对患者医疗数据的任何损害都可能导致对患者致命的错误诊断。为确保电子医疗框架中安全可靠的通信，本文提出了一种高容量双图像可分离可逆数据隐藏算法在加密域中。所有比较的可逆数据隐藏技术都已显示出主要结果，但仅在自然图像上而不是在医学图像上，因为由于大量像素具有低强度值，医学图像中可能会出现下溢问题。因此，\(log_2(u-l+1)\)覆盖图像的非种子像素处的患者信息的二进制位，不会发生任何下溢和溢出问题，从而使其能够从低强度像素中精确地嵌入和恢复信息。这一特性使我们提出的方法在医学图像上的利用真正合理。为了在接收端对电子病人信息（EPI）进行认证分析，还分别嵌入了一个脆弱的水印EPI。对于所有测试图像，观察到平均 PSNR 值为 2.38 位/像素 (bpp) 的嵌入率为 41.05 dB，这表明所提出的方法即使在高负载下也能够提供高质量的隐写图像。