A robust watermarking algorithm for medical images

Nagm, Ahmad M.; Safy, Mohammed

doi:10.11591/ijeecs.v20.i3.pp1601-1612

Cited by 6 publications

(5 citation statements)

References 25 publications

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“…We used the structural similarity index (SSIM) to compare the interpolated and the original images. SSIM tells how much one image is structurally similar to the other [38], [39]. Values between 98% and 99% were gained.…”

Section: Resultsmentioning

confidence: 99%

Brain tumor visualization for magnetic resonance images using modified shape-based interpolation method

El-Torky

Roushdy

Al-Berry

et al. 2022

IJECE

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<span>3D visualization plays an essential role in medical diagnosis and setting treatment plans especially for brain cancer. There have been many attempts for brain tumor reconstruction and visualization using various techniques. However, this problem is still considered unsolved as more accurate results are needed in this critical field. In this paper, a sequence of 2D slices of brain magnetic resonance Images was used to reconstruct a 3D model for the brain tumor. The images were automatically segmented using a wavelet multi-resolution expectation maximization algorithm. Then, the inter-slice gaps were interpolated using the proposed modified shape-based interpolation method. The method involves three main steps; transferring the binary tumor images to distance images using a suitable distance function, interpolating the distance images using cubic spline interpolation and thresholding the interpolated values to get the reconstructed slices. The final tumor is then visualized as a 3D isosurface. We evaluated the proposed method by removing an original slice from the input images and interpolating it, the results outperform the original shape-based interpolation method by an average of 3% reaching 99% of accuracy for some slice images.</span>

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Section: Resultsmentioning

confidence: 99%

Brain tumor visualization for magnetic resonance images using modified shape-based interpolation method

El-Torky

Roushdy

Al-Berry

et al. 2022

IJECE

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“…The host image that has been embedded with a watermark will experience a change in value and visual. The difference between the image before and after embedding is measured with structural similarity (SSIM) [27] which able to measure the similarity and structure of the images [28]. Table 1 shows that our method has the same value as the S matrix-based watermarking with an average SSIM of 0.9944.…”

Section: Imperceptibilitiy and Robustnessmentioning

confidence: 96%

Fast image watermarking based on signum of cosine matrix

Ernawan

Adi

Liew

et al. 2022

IJEECS

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<span>In the field of image watermarking, the singular value decomposition has good imperceptibility and robustness, but it has high complexity. It divides a host image into matrices of U, S, and V. Singular matrix S has been widely used for embedding and extracting watermark, while orthogonal matrices of U and V are used in decomposition and reconstruction. The proposed signum of cosine matrix method is carried out to eliminate the generation of the three matrices at each block and replace it with a signum of cosine matrix. The proposed signum of cosine matrix is performed faster on the decomposition and reconstruction. The image is transformed into a coefficient matrix C using the signum matrix. The C matrix values are closer to the S value of singular value decomposition which can preserve high quality of the watermarked image. The experimental results show that our method is able to produce similar imperceptibility and robustness level of the watermarked image with less computational time.</span>

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“…This work is an extension to Nagm & Safy (2020) but the steganography process is carried out in the spatial domain. Through this work, we tried to prove the effectiveness of the proposed watermark in the face of the intentional alteration of patient data not only in the frequency domain but also in the spatial domain.…”

Section: Literature Reviewmentioning

confidence: 99%

Protection of the patient data against intentional attacks using a hybrid robust watermarking code

Nagm

Elwan²

2021

PeerJ Computer Science

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The security of patient information is important during the transfer of medical data. A hybrid spatial domain watermarking algorithm that includes encryption, integrity protection, and steganography is proposed to strengthen the information originality based on the authentication. The proposed algorithm checks whether the patient’s information has been deliberately changed or not. The created code is distributed at every pixel of the medical image and not only in the regions of non-interest pixels, while the image details are still preserved. To enhance the security of the watermarking code, SHA-1 is used to get the initial key for the Symmetric Encryption Algorithm. The target of this approach is to preserve the content of the image and the watermark simultaneously, this is achieved by synthesizing an encrypted watermark from one of the components of the original image and not by embedding a watermark in the image. To evaluate the proposed code the Least Significant Bit (LSB), Bit2SB, and Bit3SB were used. The evaluation of the proposed code showed that the LSB is of better quality but overall the Bit2SB is better in its ability against the active attacks up to a size of 2*2 pixels, and it preserves the high image quality.

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A robust watermarking algorithm for medical images

Cited by 6 publications

References 25 publications

Brain tumor visualization for magnetic resonance images using modified shape-based interpolation method

Brain tumor visualization for magnetic resonance images using modified shape-based interpolation method

Fast image watermarking based on signum of cosine matrix

Protection of the patient data against intentional attacks using a hybrid robust watermarking code

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