Visible to the public Reversible Data Hiding Based Key Region Protection Method in Medical Images

TitleReversible Data Hiding Based Key Region Protection Method in Medical Images
Publication TypeConference Paper
Year of Publication2019
AuthorsLi, Jian, Zhang, Zelin, Li, Shengyu, Benton, Ryan, Huang, Yulong, Kasukurthi, Mohan Vamsi, Li, Dongqi, Lin, Jingwei, Borchert, Glen M., Tan, Shaobo, Ma, Bin, Yang, Meihong, Huang, Jingshan
Conference Name2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Date Publishednov
Keywordscryptography, cyber physical systems, data encapsulation, data leakage, data privacy, encryption key, high-texture area, Image coding, image encryption, image restoration, image retrieval, image segmentation, image watermarking, information loss, information-hiding, key region, key region protection method, lesion areas, medical image copyright, medical image data, medical image processing, medical images, open network environment, original image, original key regions, original lesion information, patient privacy, patient-sensitive information, privacy issues, pubcrawl, QR code, QR codes, Resiliency, reversible data hiding, reversible data-hiding algorithm, Selective Encryption, texture complexity
AbstractThe 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 information-hiding 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 data-hiding algorithm is used to embed the contents from the lesion areas into a high-texture 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 patient-sensitive information.
Citation Keyli_reversible_2019