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A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology.
Li, Jian; Zhang, Zelin; Li, Shengyu; Benton, Ryan; Huang, Yulong; Kasukurthi, Mohan Vamsi; Li, Dongqi; Lin, Jingwei; Borchert, Glen M; Tan, Shaobo; Li, Gang; Ma, Bin; Yang, Meihong; Huang, Jingshan.
Afiliación
  • Li J; Qilu University of Technology (Shandong Academy of Science), Shandong Provincial Key Laboratory of Computer Networks Jinan, Jinan, China.
  • Zhang Z; Qilu University of Technology (Shandong Academy of Science), Shandong Provincial Key Laboratory of Computer Networks Jinan, Jinan, China.
  • Li S; School of Computing, University of South Alabama, Mobile, AL, 36688, USA.
  • Benton R; School of Computing, University of South Alabama, Mobile, AL, 36688, USA.
  • Huang Y; College of Allied Health Professions, University of South Alabama, Mobile, AL, 36608, USA.
  • Kasukurthi MV; School of Computing, University of South Alabama, Mobile, AL, 36688, USA.
  • Li D; School of Computing, University of South Alabama, Mobile, AL, 36688, USA.
  • Lin J; Ocean School, Fuzhou University, Fuzhou, China.
  • Borchert GM; College of Medicine, University of South Alabama, Mobile, AL, 36688, USA.
  • Tan S; School of Computing, University of South Alabama, Mobile, AL, 36688, USA.
  • Li G; Qilu University of Technology (Shandong Academy of Science), Shandong Provincial Key Laboratory of Computer Networks Jinan, Jinan, China.
  • Ma B; Qilu University of Technology (Shandong Academy of Science), Shandong Provincial Key Laboratory of Computer Networks Jinan, Jinan, China. mab@qlu.edu.cn.
  • Yang M; Qilu University of Technology (Shandong Academy of Science), Shandong Provincial Key Laboratory of Computer Networks Jinan, Jinan, China. yangmh@sdas.org.
  • Huang J; School of Computing, University of South Alabama, Mobile, AL, 36688, USA. huang@southalabama.edu.
BMC Med Inform Decis Mak ; 20(Suppl 14): 297, 2020 12 15.
Article en En | MEDLINE | ID: mdl-33323108
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 better the quality and vice versa. This allows the encryptor to control the amount of degradation as, at appropriate amounts, degradation aids in the protection of the image. CONCLUSIONS: As shown in the experimental results, the proposed method allows for (a) the safe transmission and storage of medical image data, (b) the full recovery (no information loss) of sensitive regions within the medical image following encryption, and (c) meta-data about the patient and image to be stored within and recovered from the public image.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Seguridad Computacional Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Seguridad Computacional Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: China