Protecting the safety of digital information, medical devices, and applications from unauthorized access, theft, or fraud is the primary objective of security measures. The availability of trustworthy media reports at the appropriate times is also crucial. Nevertheless, eHealth systems are vulnerable to numerous threats caused by media bias. This research presents deep learning-based dual watermarking that can protect medical image copyrights using a single encoder and dual decoder. The first step is to create an embedded network that covertly uses a prep and hiding network to insert medical images into the carrier image. The second step is the reveal network, which is used to retrieve the hidden images. The proposed method is successfully applied to chest X-ray images, incorporating several attacks. It demonstrates strong resilience, as seen by a NC value of 0.9961. Additionally, it possesses an invisibility feature, achieving a PSNR of 80.18dB. Experimental results show that the suggested method is superior to previous approaches in terms of PSNR and NC.