A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology
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RESEARCH
A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology Jian Li1, Zelin Zhang1, Shengyu Li2, Ryan Benton2, Yulong Huang3, Mohan Vamsi Kasukurthi2, Dongqi Li2, Jingwei Lin4, Glen M. Borchert5, Shaobo Tan2, Gang Li1, Bin Ma1*, Meihong Yang1* and Jingshan Huang2,5*
From 10th International Workshop on Biomedical and Health Informatics San Diego, CA, USA. 18-20 November 2019
Abstract Background: Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforementioned issues, along with the dangers of data/information leakage. Possible solutions in the past have included the utilization of information-hiding and image-encryption technologies; however, these methods can cause difficulties when attempting to recover the original images. Methods: In this work, we developed an algorithm for protecting medical image key regions. Coefficient of variation is first employed to identify key regions, a.k.a. image lesion areas; then additional areas are processed as blocks and texture complexity is analyzed. Next, our novel reversible data-hiding algorithm embeds lesion area contents into a high-texture area, after which an Arnold transformation is utilized to protect the original lesion information. After this, we use image basic information ciphertext and decryption parameters to generate a quick response (QR) code used in place of original key regions. Results: The approach presented here allows for the storage (and sending) of medical image data within open network environments, while ensuring only authorized personnel are able to recover sensitive patient information (both image and meta-data) without information loss. Discussion: Peak signal to noise ratio and the Structural Similarity Index measures show that the algorithm presented in this work can encrypt and restore original images without information loss. Moreover, by adjusting the threshold and the Mean Squared Error, we can control the overall quality of the image: the higher the threshold, the
*Correspondence: [email protected]; [email protected]; [email protected] 1 Qilu University of Technology (Shandong Academy of Science), Shandong Provincial Key Laboratory of Computer Networks Jinan, Jinan, China 5 College of Medicine, University of South Alabama, Mobile, AL 36688, USA Full list of author information is available at the end of the article © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless i
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