Abstract
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.
Highlights
Today, the role of computers in a wide range of occupations is critical to success, because computer-assisted technologies provide rapid and accurate results in every industry
Tab. 5 shows the results of the evaluation of the NIfTI medical image attack, and the findings show that the proposed technique for NIfTI image is effective
The digital image watermarking commonly used in the medical imaging in the field of teleradiology for the medical image authentication purpose while preserving the integrity of the medical data
Summary
The role of computers in a wide range of occupations is critical to success, because computer-assisted technologies provide rapid and accurate results in every industry. Images may be intentionally or unintentionally distorted during medical image generation and communication, which can have serious consequences for patient diagnosis [2] For the researcher, this is the moment of truth: It is a difficult task to maintain the delicate medical image’s integrity and authenticity in an unprotected network. It is critical to use a strong watermarking method in the NIfTI images to provide the necessary medical diagnosis in the healthcare system [5]. LL uses more of the image’s energy in their factorized watermark, and so would be the best choice for that application This proposed system is extremely resilient to noise attacks and various formatting changes.
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