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Robust Watermarking Scheme for NIfTI Medical Images

Abhishek Kumar1,5, Kamred Udham Singh2, Visvam Devadoss Ambeth Kumar3, Tapan Kant4, Abdul Khader Jilani Saudagar5,*, Abdullah Al Tameem5, Mohammed Al Khathami5, Muhammad Badruddin Khan5, Mozaherul Hoque Abul Hasanat5, Khalid Mahmood Malik6

1 School of Computer Science and IT, JAIN (Deemed to be University), Bangalore, 560069, India
2 Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, 701, Taiwan
3 Department of Computer Science & Engineering, Panimalar Engineering College, Anna University, Chennai, 600123, India
4 Patna Women's College, Patna, 800001, India
5 Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
6 Department of Computer Science and Engineering, Oakland University, Rochester, 48309, USA

* Corresponding Author: Abdul Khader Jilani Saudagar. Email: email

(This article belongs to this Special Issue: Edge Computing and Machine Learning for Improving Healthcare Services)

Computers, Materials & Continua 2022, 71(2), 3107-3125.


Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI) technologies are widely used in medical field. Within the last few months, due to the increased use of CT scans, millions of patients have had their CT scans done. So, as a result, images showing the Corona Virus for diagnostic purposes were digitally transmitted over the internet. The major problem for the world health care system is a multitude of attacks that affect copyright protection and other ethical issues as images are transmitted over the internet. As a result, it is important to apply a robust and secure watermarking technique to these images. Notably, watermarking schemes have been developed for various image formats, including .jpg, .bmp, and .png, but their impact on NIfTI (Neuroimaging Informatics Technology Initiative) images is not noteworthy. A watermarking scheme based on the Lifting Wavelet Transform (LWT) and QR factorization is presented in this paper. When LWT and QR are combined, the NIfTI image maintains its inherent sensitivity and mitigates the watermarking scheme's robustness. Multiple watermarks are added to the host image in this approach. Measuring the performance of the graphics card is done by using PSNR, SSIM, Q (a formula which measures image quality), SNR, and Normalized correlation. The watermarking scheme withstands a variety of noise attacks and conversions, including image compression and decompression.


Cite This Article

A. Kumar, K. Udham Singh, V. Devadoss Ambeth Kumar, T. Kant, A. Khader Jilani Saudagar et al., "Robust watermarking scheme for nifti medical images," Computers, Materials & Continua, vol. 71, no.2, pp. 3107–3125, 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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