Main Article Content
Abstract
This paper develops a fragile, reversible watermarking technique to detect accidental and intentional alterations in DICOM medical images. A fragile method is adopted to detect any manipulation applied to medical images, while reversibility ensures the recovery of the original unaltered image at extraction. The proposed approach automatically segments medical images into Region of Interest (ROI) and Region of Non-Interest (RONI), extracts authentication data from the DICOM header, and generates a digital signature of the image. The method combines integrity and authentication data and inserts them into the edge areas within the ROI, implementing the Prediction Error Expansion (PEE) technique and Canny edge detection. During extraction, the embedded watermark and the original unmanipulated image are restored without knowing the pixel locations used to hide the watermark data. The method was assessed using twelve 16-bit DICOM images, including MRI and CT, with a 512x512 pixel size. The experimental results yielded an average PSNR of 97.19 dB and an average SSIM of 0.999996, with an average watermark length of 7835 bits per image. The proposed method also fully met the reversibility requirement by recovering both the original unaltered images and the embedded watermark data. Fragility evaluation showed that manipulations of watermarked images can be detected via alterations in the retrieved watermark. The achieved results demonstrate the effectiveness of the proposed technique in maintaining visual image quality while ensuring reversibility, integrity, and authenticity in the conducted experiments.
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Article Details
References
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- P. Soille, Morphological image analysis: principles and applications. 2nd ed. Springer. Berlin, Germany, 2013.doi:10.1007/978-3-662-05088-0.
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- J. Tian, "Reversible watermarking by difference expansion," in Proceedings of workshop on multimedia and security, 2002, pp. 19-22.
- A. F. Qasim, F. Meziane, and R. Aspin, "A reversible and imperceptible watermarking scheme for MR images authentication," in Proceedings of the 24th International Conference on Automation and Computing (ICAC'2018), Newcastle upon Tyne, UK, 2018: IEEE, doi: 10.23919/IConAC.2018.8749000.
- J. E. Mosco-Garcia, M. Cedillo-Hernandez, and H. Shouno, "Data Hiding for Clinical Information in DICOM Images via Reversible Halftone Fragile Watermarking," in New Trends in Intelligent Software Methodologies, Tools and Techniques: Proceedings of the 24th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques (SoMeT_25), 2025: SAGE Publications 1 Oliver's Yard, 55 City Road, London, EC1Y 1SP, pp. 469-482, doi: https://doi.org/10.3233/FAIA2505.
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- Atta-ur-Rahman, K. Sultan, N. Aldhafferi, A. Alqahtani, and M. Mahmud, "Reversible and fragile watermarking for medical images," Computational and mathematical methods in medicine, vol. 2018, pp. 1-7, 2018, doi: https://doi.org/10.1155/2018/3461382.
References
T. M. Godinho, L. M. Silva, and C. Costa, "An automation framework for PACS workflows optimization in shared environments," in 10th Iberian Conference on Information Systems and Technologies (CISTI), Aveiro, Portugal, 2015: IEEE, pp. 1-7, doi:10.1109/CISTI.2015.7170422.
O. S. Pianykh, Digital imaging and communications in medicine (DICOM): a practical introduction and survival guide, 2nd ed ed. 2nd ed. Springer. Berlin, Germany, 2009.doi:https://doi.org/10.1007/978-3-540-74571-6_5.
N. A. Memon, A. Chaudhry, M. Ahmad, and Z. A. Keerio, "Hybrid watermarking of medical images for ROI authentication and recovery," International Journal of Computer Mathematics, vol. 88, no. 10, pp. 2057-2071, 2011, doi: abs/10.1080/00207160.2010.543677.
R. Priya and V. Sadasivam, "A survey on watermarking techniques, requirements, applications for medical images," Journal of Theoretical and Applied Information Technology, vol. 65, no. 1, pp. 103-120, 2014.
S. C. Liew and J. M. Zain, "Tamper localization and lossless recovery watermarking scheme," in Software Engineering and Computer Systems: Springer, 2011, pp. 555-566.doi:https://doi.org/10.1007/978-3-642-22170-5_48.
L. O. M. Kobayashi, S. S. Furuie, and P. S. L. M. Barreto, "Providing integrity and authenticity in DICOM images: a novel approach," IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 4, pp. 582-589, 2009, doi: 10.1109/TITB.2009.2014751.
J. Guru and H. Damecha, "Digital watermarking classification: a survey," International Journal of Computer Science Trends and Technology (IJCST) vol, vol. 5, pp. 8-13, 2014.
A. F. Qasim, F. Meziane, and R. Aspin, "Digital watermarking: Applicability for developing trust in medical imaging workflows state of the art review," Computer Science Review, vol. 27, pp. 45-60, 2018, doi: 10.1016/j.cosrev.2017.11.003.
A. Khan, A. Siddiqa, S. Munib, and S. A. Malik, "A recent survey of reversible watermarking techniques," Information sciences, vol. 279, pp. 251-272, 2014, doi: https://doi.org/10.1016/j.ins.2014.03.118.
Y. Yang, W. Zhang, D. Liang, and N. Yu, "A ROI-based high-capacity reversible data hiding scheme with contrast enhancement for medical images," Multimedia Tools and Applications, vol. 77, no. 14, pp. 18043-18065, 2018, doi: https://doi.org/10.1007/s11042-017-4444-0.
L. Tanwar and J. Panda, "Hybrid reversible watermarking algorithm using histogram shifting and pairwise prediction error expansion," Multimedia Tools and Applications, vol. 83, no. 8, pp. 22075-22097, 2024, doi: https://doi.org/10.1007/s11042-023-15508-5.
M. Arsalan, S. A. Malik, and A. Khan, "Intelligent reversible watermarking in integer wavelet domain for medical images," Journal of Systems and Software, vol. 85, no. 4, pp. 883-894, 2012, doi: https://doi.org/10.1016/j.jss.2011.11.005.
M. U. Celik, G. Sharma, A. M. Tekalp, and E. Saber, "Lossless generalized-LSB data embedding," IEEE transactions on image processing, vol. 14, no. 2, pp. 253-266, 2005, doi: 10.1109/TIP.2004.840686.
G. Gao, X. Wan, S. Yao, Z. Cui, C. Zhou, and X. Sun, "Reversible data hiding with contrast enhancement and tamper localization for medical images," Information Sciences, vol. 385, pp. 250-265, 2017, doi: https://doi.org/10.1016/j.ins.2017.01.009.
T.-S. Nguyen, C.-C. Chang, and N.-T. Huynh, "A novel reversible data hiding scheme based on difference-histogram modification and optimal EMD algorithm," Journal of Visual Communication and Image Representation, vol. 33, pp. 389-397, 2015, doi: 10.1016/j.jvcir.2015.10.008.
A. Khan and S. A. Malik, "A high capacity reversible watermarking approach for authenticating images: Exploiting down-sampling, histogram processing, and block selection," Information Sciences, vol. 256, pp. 162-183, 2014, doi: https://doi.org/10.1016/j.ins.2013.07.035.
W. He, K. Zhou, J. Cai, L. Wang, and G. Xiong, "Reversible data hiding using multi-pass pixel value ordering and prediction-error expansion," Journal of Visual Communication and Image Representation, vol. 49, pp. 351-360, 2017, doi: 10.1016/j.jvcir.2017.10.001.
B. Lei, E. L. Tan, S. Chen, D. Ni, T. Wang, and H. Lei, "Reversible watermarking scheme for medical image based on differential evolution," Expert Syst. Appl., vol. 41, no. 7, pp. 3178-3188, 2014. [Online]. Available: http://ac.els-cdn.com/S0957417413009317/1-s2.0-S0957417413009317-main.pdf?_tid=e3850d26-0260-11e6-ab01-00000aab0f6c&acdnat=1460652763_54ccd2807cb900d7165673f21f8bd235.
A. Roček, K. Slavíček, O. Dostál, and M. Javorník, "A new approach to fully-reversible watermarking in medical imaging with breakthrough visibility parameters," Biomedical Signal Processing and Control, vol. 29, pp. 44-52, 2016, doi: https://doi.org/10.1016/j.bspc.2016.05.005.
G. Xuan, C. Yang, Y. Zhen, Y. Q. Shi, and Z. Ni, "Reversible data hiding using integer wavelet transform and companding technique," in International Workshop on Digital Watermarking, 2004: Springer, pp. 115-124, doi: https://doi.org/10.1007/978-3-540-31805-7_10.
J. Tian, "Reversible data embedding using a difference expansion," IEEE transactions on circuits and systems for video technology, vol. 13, no. 8, pp. 890-896, 2003, doi: 10.1109/TCSVT.2003.815962.
A. M. Alattar, "Reversible watermark using difference expansion of triplets," in International Conference on Image Processing (Cat. No.03CH37429), Barcelona, Spain, 2003: IEEE, pp. 501-504, doi: 10.1109/ICIP.2003.1247008.
A. M. Alattar, "Reversible watermark using difference expansion of quads," in International Conference on Acoustics, Speech, and Signal Processing (ICASSP'04), Montreal, Que., Canada, 2004: IEEE, pp. 377-380, doi: 10.1109/ICASSP.2004.1326560.
A. M. Alattar, "Reversible watermark using the difference expansion of a generalized integer transform," IEEE Transactions on Image Processing, vol. 13, no. 8, pp. 1147-1156, 2004, doi: 10.1109/TIP.2004.828418.
A. F. Qasim, R. Aspin, F. Meziane, and P. Hogg, "ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images," Multimedia Tools and Applications, vol. 78, no. 12, pp. 16433-16463, 2019, doi: https://doi.org/10.1007/s11042-018-7029-7.
S. Bhalerao, I. A. Ansari, and A. Kumar, "A reversible medical image watermarking for ROI tamper detection and recovery," Circuits, Systems, and Signal Processing, vol. 42, no. 11, pp. 6701-6725, 2023, doi: https://doi.org/10.1007/s00034-023-02416-0.
B. Chidirala and B. Acharya, "Prediction error expansion based reversible watermarking scheme in higher order pixels," Sādhanā, vol. 49, no. 3, p. 227, 2024, doi: https://doi.org/10.1007/s12046-024-02569-x.
A. Arham, S. A. I. Alfarozi, and H. A. Nugroho, "A high-capacity reversible watermarking technique using bit-level expansion and pixel shifting," Communications in Science and Technology, vol. 10, no. 2, pp. 477-492, 2025, doi: 10.21924/cst.
A. Arham, T. B. Adji, S. A. I. Alfarozi, and H. A. Nugroho, "Reversible watermarking for medical images using ROI-based tamper localization and recovery," Franklin Open, p. 100545, 2026, doi: https://doi.org/10.1016/j.fraope.2026.100545.
A. M. Hasan, F. Meziane, and M. A. Kadhim, "Automated segmentation of tumours in MRI brain scans," in Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC), Rome, Italy, 2016, pp. 55-62, doi: 10.5220/0005625900550062.
P. Soille, Morphological image analysis: principles and applications. 2nd ed. Springer. Berlin, Germany, 2013.doi:10.1007/978-3-662-05088-0.
L.-H. Gong, C. Tian, W.-P. Zou, and N.-R. Zhou, "Robust and imperceptible watermarking scheme based on Canny edge detection and SVD in the contourlet domain," Multimedia tools and applications, vol. 80, no. 1, pp. 439-461, 2021, doi: https://doi.org/10.1007/s11042-020-09677-w.
J. Tian, "Reversible watermarking by difference expansion," in Proceedings of workshop on multimedia and security, 2002, pp. 19-22.
A. F. Qasim, F. Meziane, and R. Aspin, "A reversible and imperceptible watermarking scheme for MR images authentication," in Proceedings of the 24th International Conference on Automation and Computing (ICAC'2018), Newcastle upon Tyne, UK, 2018: IEEE, doi: 10.23919/IConAC.2018.8749000.
J. E. Mosco-Garcia, M. Cedillo-Hernandez, and H. Shouno, "Data Hiding for Clinical Information in DICOM Images via Reversible Halftone Fragile Watermarking," in New Trends in Intelligent Software Methodologies, Tools and Techniques: Proceedings of the 24th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques (SoMeT_25), 2025: SAGE Publications 1 Oliver's Yard, 55 City Road, London, EC1Y 1SP, pp. 469-482, doi: https://doi.org/10.3233/FAIA2505.
E. T. Mharakurwa, "A prediction error nonlinear difference expansion reversible watermarking for integrity and authenticity of DICOM medical images," International Journal of Advanced Computer Science and Applications, 2022, doi: 10.14569/IJACSA.2022.0130326.
N. Memon and A. Alzahrani, "Prediction‐based reversible watermarking of CT scan images for content authentication and copyright protection. IEEE Access 8, 75448–75462 (2020). Paper," ed, 2020.doi:10.1109/ACCESS.2020.2989175.
Atta-ur-Rahman, K. Sultan, N. Aldhafferi, A. Alqahtani, and M. Mahmud, "Reversible and fragile watermarking for medical images," Computational and mathematical methods in medicine, vol. 2018, pp. 1-7, 2018, doi: https://doi.org/10.1155/2018/3461382.