Reversible Data Hiding Based Key Region Protection Method in Medical Images The transmission of medical image data in an open network environment is subject to privacy issues including patient privacy and data leakage. In the past, image encryption and informationhiding technology have been used to solve such security problems. But these methodologies, in general, suffered from difficulties in retrieving original images. We present in this paper an algorithm to protect key regions in medical images. First, coefficient of variation is used to locate the key regions, a.k.a. the lesion areas, of an image; other areas are then processed in blocks and analyzed for texture complexity. Next, our reversible datahiding algorithm is used to embed the contents from the lesion areas into a hightexture area, and the Arnold transformation is performed to protect the original lesion information. In addition to this, we use the ciphertext of the basic information about the image and the decryption parameter to generate the Quick Response (QR) Code to replace the original key regions. Consequently, only authorized customers can obtain the encryption key to extract information from encrypted images. Experimental results show that our algorithm can not only restore the original image without information loss, but also safely transfer the medical image copyright and patientsensitive information.

An improved DWTSVD domain watermarking for medical information security Abstract   Exchange of patient record over network required a technique to guarantee security and privacy for telehealth services. This paper presents an improved watermarking technique capable of providing protection of patient data by embedding multiwatermarks in medical cover image using DWTSVD domain. Prior to embedding, Hamming code is applied to text watermark in order to reduce channel noise distortion for the sensitive data. After embedding, the watermarked medical image is encrypted then compressed. Out of two encryption method and three compression scheme tested, combination of ChaoticLZW shows the best performance. However, HyperChaoticLZW combination is more robust against Gaussian, JPEG compression, speckle noise and histogram equalization attacks. We illustrate the good results in terms of objective and subjective evaluation, and verify its robustness for various attacks while maintaining imperceptibility, security and compression ratio. Experimental results demonstrate that the suggested technique archives high robustness against attacks in comparison to the other scheme for medical images.