Abstract
Medical systems, such as PACS or scanners, are vulnerable to security and forgery attacks. Consequently, medical records, such as patient information and medical imagery, can be easily leaked or forged. Reversible watermarking is an efficient solution used to protect medical records. However, previous studies have not sufficiently addressed medical applications. This study proposes an adaptive reversible watermarking algorithm that is directly applicable to medical systems that preserves the quality of medical imagery. In particular, the characteristics of medical imagery are considered. Once object and background regions are segmented, the reversible watermarking algorithm is applied based on an estimated error expansion approach. The watermark is embedded by expanding the estimated error from adjacent pixels. This watermark can include patient information or a hash code to detect forgery. When the watermark is extracted, original imagery is perfectly reconstructed without any quality degradation. Inherent over- and underflow problems are solved using an error pre-compensation technique. With the use of medical images from MRI, CT, and X-ray scanners, intensive experiments are performed to analyze the performance of the proposed algorithm with respect to capacity, perceptual quality, and reconstruction rate.
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References
Abdeldaim AM, Sahlol AT, Elhoseny M, Hassanien AE (2018) Computer-aided acute lymphoblastic leukemia diagnosis system based on image analysis. In: Hassanien A, Oliva D (eds) Advances in soft computing and machine learning in image processing. Studies in computational intelligence, vol 730. Springer, pp 131–147. https://doi.org/10.1007/978-3-319-63754-9_7
Alattar AM (2004) Reversible watermark using the difference expansion of a generalized integer transform. IEEE Trans Image Process 13(8):1147–1156. https://doi.org/10.1109/TIP.2004.828418
Al-Dmour H, Al-Ani A (2016) Quality optimized medical image information hiding algorithm that employs edge detection and data coding. Comput Methods Prog Biomed 127:24–43. https://doi.org/10.1016/j.cmpb.2016.01.011
Celik MU, Sharma G, Tekalp AM, Saber E (2005) Lossless generalized-LSB data embedding. IEEE Trans Image Process 14(2):253–266. https://doi.org/10.1109/TIP.2004.840686
Coatrieux G, Pan W, Cuppens N, Cuppens F, Roux C (2012) Reversible watermarking based on invariant image classification and dynamic histogram shifting. IEEE Trans Inf Forensics Security 8(1):111–120. https://doi.org/10.1109/TIFS.2012.2224108
Dou W, Poh CL, Guan YL (2012) An improved tamper detection and localization scheme for volumetric DICOM images. J Digit Imaging 25(6):751–763. https://doi.org/10.1007/s10278-012-9518-y
Elhoseny M, Ramirez-Gonzalez G, Abu-Elnasr OM, Shawkat SA, Arunkumar N, Farouk A (2018) Secure medical data transmission model for IoT-based healthcare systems. IEEE Access 6:20596–20608. https://doi.org/10.1109/ACCESS.2018.2817615
Eltoukhy MM, Elhoseny M, Hosny KM, Singh AK (2018) Computer aided detection of mammographic mass using exact Gaussian-Hermite moments. J Ambient Intell Humaniz Comput:1–9. https://doi.org/10.1007/s12652-018-0905-1
Eswaraiah R, Sreenivasa RE (2014) Medical image watermarking technique for accurate tamper detection in ROI and exact recovery of ROI. Int J Telemed Appl 2014:1–10. https://doi.org/10.1155/2014/984646
Fridrich J, Goljan J, Du R (2002) Lossless data embedding-new paradigm in digital watermarking. EURASIP J Adv Signal Process 2002:185–196. https://doi.org/10.1155/S1110865702000537
Gao G, Wan W, Yao S, Cui Z, Zhou C, Sun X (2017) Reversible data hiding with contrast enhancement and tamper localization for medical images. Inf Sci 285(C):250–265. https://doi.org/10.1016/j.ins.2017.01.009
Kim KS, Lee MJ, Lee HY, Lee HK (2009) Reversible data hiding exploiting spatial correlation between sub-sampled images. Pattern Recogn 42(11):3083–3096. https://doi.org/10.1016/j.patcog.2009.04.004
Lee HY (2014) Reversible data hiding based on prediction-error expansion and error pre-compensation. Journal of Convergence Information Technology 8(16):48–62
Lee HY, Kim H, Lee HK (2006) Robust image watermarking using local invariant features. Opt Eng 45(3):037002. https://doi.org/10.1117/1.2181887
Lee S, Yoo CD, Kalker T (2007) Reversible image watermarking based on integer-to-integer wavelet transform. IEEE Trans Inf Forensics Security 2(3):321–330. https://doi.org/10.1109/TIFS.2007.905146
Lee HY, Codella N, Cham M, Prince M, Weinsaft J, Wang Y (2008) Left ventricle segmentation using graph searching on intensity and gradient and a priori knowledge (lvGIGA) for short axis cardiac MRI. J Magn Reson Imaging 28(1):1393–1401. https://doi.org/10.1002/jmri.21586
Lee HY, Codella N, Cham M, Weinsaft J, Wang Y (2010) Automatic left ventricle segmentation using iterative thresholding and active contour model with adaptation on short-Axis cardiac MRI. IEEE Trans Biomed Eng 75(4):905–913. https://doi.org/10.1109/TBME.2009.2014545
Lia M, Poovendrana R, Narayanan S (2005) Protecting patient privacy against unauthorized release of medical images in a group communication environment. Comput Med Imaging Graph 29:367–383. https://doi.org/10.1016/j.compmedimag.2005.02.003
Mousavi SM, Naghsh A, Abu-Bakar SAR (2014) Watermarking techniques used in medical images: a survey. J Digit Imaging 27(6):714–729. https://doi.org/10.1007/s10278-014-9700-5
Ni Z, Shi YQ, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circuits Syst Video Technol 16(3):354–362. https://doi.org/10.1109/TCSVT.2006.869964
Nyeem H, Boles W, Boyd C (2013) A review of medical image watermarking requirements for teleradiology. J Digit Imaging 26(2):326–343. https://doi.org/10.1007/s10278-012-9527-x
Parah SA, Ahad F, Sheikh JA, Bhat GM (2017) Hiding clinical information in medical images: a new high capacity and reversible data hiding technique. J Biomed Inform 66:214–230. https://doi.org/10.1016/j.jbi.2017.01.006
Priyanka MS (2017) Region-based hybrid medical image watermarking for secure telemedicine applications. Multimed Tools Appl 76(3):3617–3647. https://doi.org/10.1007/s11042-016-3913-1
Shehab A, Elhoseny M, Muhammad K, Sangaiah AK, Yang P, Huang H, Hou G (2018) Secure and robust fragile watermarking scheme for medical images. IEEE Access 6(1):10269–10278. https://doi.org/10.1109/ACCESS.2018.2799240
Shih FY, Wu YT (2005) Robust watermarking and compression for medical images based on genetic algorithms. Inf Sci 175:200–216. https://doi.org/10.1016/j.ins.2005.01.013
Tan CK, Ng JC, Xu X, Poh CL, Guan YL, Sheah K (2011) Security protection of DICOM medical images using dual-layer reversible watermarking with tamper detection capability. J Digit Imaging 24(3):528–540. https://doi.org/10.1007/s10278-010-9295-4
Thakur S, Singh AK, Ghrera SP, Elhoseny M (2018) Multi-layer security of medical data through watermarking and chaotic encryption for tele-health applications. Multimed Tools Appl:1–14. https://doi.org/10.1007/s11042-018-6263-3
Thanki R, Borra S, Dwivedi V, Borisagar K (2017) An efficient medical image watermarking scheme based on FDCuT–DCT. Eng Sci Technol Int J 20:1366–1379. https://doi.org/10.1016/j.jestch.2017.06.001
Ustubioglu A, Ulutas G (2017) A new medical image watermarking technique with finer tamper localization. J Digit Imaging 30(6):665–680. https://doi.org/10.1007/s10278-017-9960-y
Wang D, Chen D, Ma B, Xu L, Zhang J (2017) A high capacity spatial domain data hiding scheme for medical images. J Signal Process Sys 87(2):215–227. https://doi.org/10.1007/s11265-016-1169-7
Wu HT, Huang J, Shi YQ (2015) A reversible data hiding method with contrast enhancement for medical images. J Vis Commun Image Represent 31(C):146–153. https://doi.org/10.1016/j.jvcir.2015.06.010
Yang Y, Zhang W, Liang D, Yu N (2016) Reversible data hiding in medical images with enhanced contrast in texture area.Digit Signal Process 52:13–24. https://doi.org/10.1016/j.dsp.2016.02.006
Yeo DG, Lee HY, Kim BM (2011) High capacity reversible watermarking using differential histogram shifting and predicted error compensation. J Electron Imaging 20(1). https://doi.org/10.1117/1.3532833
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This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1 A1B03030432).
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Lee, HY. Adaptive reversible watermarking for authentication and privacy protection of medical records. Multimed Tools Appl 78, 19663–19680 (2019). https://doi.org/10.1007/s11042-019-7322-0
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DOI: https://doi.org/10.1007/s11042-019-7322-0