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Secure management of DICOM images via reversible data hiding, contrast enhancement and visible-imperceptible watermarking

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Abstract

Purpose

This paper proposes a novel algorithm that fuses visible-imperceptible watermarking and reversible data hiding with contrast enhancement to improve the medical image management in terms of avoid detachment between data of an electronic patient record and its corresponding medical image as well as authentication to identify the image source.

Methods

Medical data management has progressed due to the advances in communication and information technologies. Scientific literature reports several methods for contribute to the improvement of medical image management, many of these based on watermarking and reversible data hiding. The choice either one or the other depends on the application and requirements. The proposed method employs visible-imperceptible watermarking, to conceal in an imperceptible manner a set of watermarks in the spatial domain to perform authentication revealing its content by a naked eye via a contrast enhancement provided by a reversible data hiding technique that the same time hide medical data into the watermark logos to perform the tasks to avoid detachment. The above operations are invertible and can be used on demand, either for obtain a clear image to the medical diagnosis or for obtain a protected image to improve its use.

Results

Experimental results show the contribution of the proposed scheme and its efficiency regarding medical image management in terms of imperceptibility, robustness, and payload.

Conclusions

The efficiency of the proposed method was confirmed by performing several experiments comparing its performance with current state-of-the-art works. Our proposal preserves the native DICOM format with its original grayscale resolution.

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Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

References

  1. National Electrical Manufacturers Association (NEMA). DICOM Security. 1 Page. [Online]. 2023. Available at https://www.dicomstandard.org/using/security/.

  2. Coatrieux G, Quantin C, et al. Watermarking medical images with anonymous patient identification to verify authenticity. In: Studies in health technology and informatics, vol. 136. IOS Press; 2008. p. 667–72.

    Google Scholar 

  3. Qasim AF, Meziane F, Aspin R. Digital watermarking: Applicability for developing trust in medical imaging workflows state of the art review. Comput Sci Rev. 2018;27:45–60. https://doi.org/10.1016/j.cosrev.2017.11.003.

    Article  MathSciNet  Google Scholar 

  4. Mousavi SM, Naghsh A, Abu-Bakar SAR. Watermarking techniques used in medical images: a Survey. J Digit Imaging. 2014;27:714–29. https://doi.org/10.1007/s10278-014-9700-5.

    Article  Google Scholar 

  5. Cedillo-Hernandez M, Cedillo-Hernandez A, Nakano-Miyatake M, Perez-Meana H. Improving the management of medical imaging by using robust and secure dual watermarking. Biomed Signal Process Control. 2020;56:101695. https://doi.org/10.1016/j.bspc.2019.101695.

    Article  Google Scholar 

  6. Barni M, Bartolini F. Applications. In: Watermarking systems engineering: enabling digital assets security and other applications. Boca Raton: CRC Press; 2004. p. 23–44. https://doi.org/10.1201/9780203913512.

    Chapter  Google Scholar 

  7. Barni M, Cox I, Kalker T, Kim HJ. Digital watermarking. 2005. https://doi.org/10.1007/11551492.

    Article  Google Scholar 

  8. Cox I, Miller M, Bloom J. Applications and properties. In: Digital Watermarking. USA: Morgan Kaufmann Publishers; 2002. p. 11–39. https://www.elsevier.com/books/digital-watermarking/cox/978-1-55860-714-9.

  9. Wu X, Qiao T, Chen Y, Xu M, Zheng N, Luo X. Sign steganography revisited with robust domain selection. Signal Process. 2022;196:108522. https://doi.org/10.1016/j.sigpro.2022.108522.

    Article  Google Scholar 

  10. Valandar MY, Ayubi P, Barani MJ, Irani BY. A chaotic video steganography technique for carrying different types of secret messages. J Inf Secur Appl. 2022;66: 103160. https://doi.org/10.1016/j.jisa.2022.103160.

    Article  Google Scholar 

  11. Rostam HE, Motameni H, Enayatifar R. Privacy-preserving in the internet of things based on steganography and chaotic functions. Optik. 2022;258:168864. https://doi.org/10.1016/j.ijleo.2022.168864.

    Article  Google Scholar 

  12. Mata-Mendoza D, Nuñez-Ramirez D, Cedillo-Hernandez M, et al. An improved ROI-based reversible data hiding scheme completely separable applied to encrypted medical images. Health Technol. 2021;11:835–50. https://doi.org/10.1007/s12553-021-00562-6.

    Article  Google Scholar 

  13. Shi Y, Li X, Zhang X, Wu H, Ma B. Reversible data hiding: Advances in the past two decades. IEEE Access. 2016;4:3210–37. https://doi.org/10.1109/ACCESS.2016.2573308.

    Article  Google Scholar 

  14. Yu C, Zhang X, Wang D, Tang Z. Reversible data hiding with pairwise PEE and 2D-PEH decomposition. Signal Process. 2022;196:108527. https://doi.org/10.1016/j.sigpro.2022.108527.

    Article  Google Scholar 

  15. Vaish A, Jayswal S. A systematic review on various reversible data hiding techniques in digital images. Recent Adv CompuT Sci Commun. 2021. https://doi.org/10.2174/2666255813666200221140837.

    Article  Google Scholar 

  16. Kumar S, Gupta A, Walia GS. Reversible data hiding: A contemporary survey of state-of-the-art, opportunities and challenges. Appl Intell. 2021. https://doi.org/10.1007/s10489-021-02789-2.

    Article  Google Scholar 

  17. Jose A, Subramaniam K. Comparative analysis of reversible data hiding schemes. IET Image Process. 2020;14:2064–73. https://doi.org/10.1049/iet-ipr.2019.1066.

    Article  Google Scholar 

  18. Chuang SC, Huang CH, Wu JL. Unseen visible watermarking. In: IEEE International Conference on Image Processing, San Antonio, Texas. 2007. p. 261–4. https://doi.org/10.1109/ICIP.2007.4379296.

    Chapter  Google Scholar 

  19. Huang CH, et al. Unseen visible watermarking: a novel methodology for auxiliary information delivery via visual contents. IEEE Trans Inf For Secur. 2009;4(2):193–206. https://doi.org/10.1109/TIFS.2009.2020778.

    Article  Google Scholar 

  20. Lin PY. Imperceptible visible watermarking based on post camera histogram operation. J Syst Softw. 2014;95:194–208. https://doi.org/10.1016/j.jss.2014.04.038.

    Article  Google Scholar 

  21. Juarez-Sandoval U, et al. Digital image ownership authentication via camouflaged unseen-visible watermarking. Multimed Tools Appl. 2018;77(20):26601–34. https://doi.org/10.1007/s11042-018-5881-0.

    Article  Google Scholar 

  22. Mata-Mendoza D, Cedillo-Hernandez M, Garcia-Ugalde F, et al. Secured telemedicine of medical imaging based on dual robust watermarking. Vis Comput. 2021. https://doi.org/10.1007/s00371-021-02267-3.

    Article  Google Scholar 

  23. Juarez-Sandoval OU, Garcia-Ugalde FJ, Cedillo-Hernandez M, Ramirez-Hernandez J, Hernandez-Gonzalez L. Imperceptible–visible watermarking to information security tasks in color imaging. Mathematics. 2021;9:2374. https://doi.org/10.3390/math9192374.

    Article  Google Scholar 

  24. Nuñez-Ramirez D, Cedillo-Hernandez M, Nakano-Miyatake M, Perez-Meana H. Efficient management of ultrasound images using digital watermarking. IEEE Lat Am Trans. 2020;18(08):1398–406. https://doi.org/10.1109/TLA.2020.9111675.

    Article  Google Scholar 

  25. Wu H-T, Tang S, Huang J, Shi Y-Q. A novel reversible data hiding method with image contrast enhancement. Signal Process Image Commun. 2018;2018(62):64–73. https://doi.org/10.1016/j.image.2017.12.006.

    Article  Google Scholar 

  26. Wu H-T, Huang J, Shi Y-Q. A reversible data hiding method with contrast enhancement for medical images. J Vis Commun Image Represent. 2015;31:146–53. https://doi.org/10.1016/j.jvcir.2015.06.010.

    Article  Google Scholar 

  27. Wu H-T, Dugelay J-L, Shi Y-Q. Reversible image data hiding with contrast enhancement. IEEE Signal Process Lett. 2015;22(1):81–5. https://doi.org/10.1109/LSP.2014.2346989.

    Article  Google Scholar 

  28. Wu H-T, Mai W, Meng S, Cheung Y-M, Tang S. Reversible data hiding with image contrast enhancement based on two-dimensional histogram modification. IEEE Access. 2019;7:83332–42. https://doi.org/10.1109/Access.628763910.1109/ACCESS.2019.2921407.

    Article  Google Scholar 

  29. Nuñez-Ramirez D, Mata-Mendoza D, Cedillo-Hernandez M. Improving preprocessing in reversible data hiding based on contrast enhancement. J King Saud Univ Comput Inf Sci. 2021. https://doi.org/10.1016/j.jksuci.2021.05.007.

    Article  Google Scholar 

  30. Wu H-T, Zheng K, Huang Q, Hu J. Contrast enhancement of multiple tissues in MR brain images with reversibility. IEEE Signal Process Lett. 2021;28:160–4. https://doi.org/10.1109/LSP.2020.3048840.

    Article  Google Scholar 

  31. Gao G, Tong S, Xia Z, Wu B, Xu L, Zhao Z. Reversible data hiding with automatic contrast enhancement for medical images. Signal Process. 2021;178:107817. https://doi.org/10.1016/j.sigpro.2020.107817.

    Article  Google Scholar 

  32. Yang Y, Xiao X, Cai X, Zhang W. A secure and privacy-preserving technique based on contrast-enhancement reversible data hiding and plaintext encryption for medical images. IEEE Signal Process Lett. 2020;27:256–60. https://doi.org/10.1109/LSP.2020.2965826.

    Article  Google Scholar 

  33. Yang Y, Zhang W, Liang D, et al. A ROI-based high capacity reversible data hiding scheme with contrast enhancement for medical images. Multimed Tools Appl. 2018;77:18043–65. https://doi.org/10.1007/s11042-017-4444-0.

    Article  Google Scholar 

  34. Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern. 1979;9(1):62–6. https://doi.org/10.1109/TSMC.1979.4310076.

    Article  Google Scholar 

  35. Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Süsstrunk S. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell. 2012;34(11):2274–82. https://doi.org/10.1109/TPAMI.2012.120.

    Article  Google Scholar 

  36. Wang Z, et al. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process. 2004;13(4):600–12. https://doi.org/10.1109/TIP.2003.819861.

    Article  Google Scholar 

  37. Sheikh HR, Bovik AC. Image information, and visual quality. IEEE Trans Image Process. 2006;15(2):430–44. https://doi.org/10.1109/TIP.2005.859378.

    Article  Google Scholar 

  38. Anand A, Singh AK, Zhou H. ViMDH: visible-imperceptible medical data hiding for internet of medical things. IEEE Trans Industr Inf. 2022;19(1):849–56. https://doi.org/10.1109/TII.2022.3172622.

    Article  Google Scholar 

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Acknowledgements

Authors thanks the Instituto Politecnico Nacional (IPN) as well as the Consejo Nacional de Humanidades, Ciencias y Tecnologias de Mexico (CONAHCYT) by the support provided during the realization of this research.

Funding

This research was supported by Instituto Politecnico Nacional (IPN) as well as the Consejo Nacional de Humanidades, Ciencias y Tecnologias (CONAHCYT) of Mexico.

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Authors and Affiliations

  1. Instituto Politecnico Nacional SEPI ESIME Culhuacan, Av. Santa Ana 1000 Culhuacan CTM V, 04440, CDMX, Mexico

    Diana Nuñez-Ramirez, Eduardo Fragoso-Navarro, David Mata-Mendoza & Manuel Cedillo-Hernandez

Authors
  1. Diana Nuñez-Ramirez
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  2. Eduardo Fragoso-Navarro
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  3. David Mata-Mendoza
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  4. Manuel Cedillo-Hernandez
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Diana Nuñez-Ramirez, Eduardo Fragoso-Navarro, and David Mata-Mendoza. The first draft of the manuscript was written by Diana Nuñez-Ramirez, and Manuel Cedillo-Hernandez, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Manuel Cedillo-Hernandez.

Ethics declarations

Research involving human participants and/or animals

This research not involving human participants and/or animals.

Informed consent

All patients data in DICOM images used in this research was anonymized considering the DICOM standard in https://www.dicomstandard.org/using/security. In this way, none patients data appears in all content of the paper.

Conflict of interest

The authors declare that they have no potential conflicts of interest that could have appeared to influence the work reported in this paper.

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Nuñez-Ramirez, D., Fragoso-Navarro, E., Mata-Mendoza, D. et al. Secure management of DICOM images via reversible data hiding, contrast enhancement and visible-imperceptible watermarking. Health Technol. (2024). https://doi.org/10.1007/s12553-024-00856-5

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