Image-based decision making for reliable and proper diagnosing in NIFTI format using watermarking

Kamred Udham Singh; Akshay Kumar; Teekam Singh; Mangey Ram

doi:10.1007/s11042-022-12192-9

Image-based decision making for reliable and proper diagnosing in NIFTI format using watermarking

Multimed Tools Appl. 2022;81(27):39577-39603. doi: 10.1007/s11042-022-12192-9. Epub 2022 Apr 29.

Authors

Kamred Udham Singh^{1

2}, Akshay Kumar³, Teekam Singh⁴, Mangey Ram^{5

6}

Affiliations

¹ Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1, University Road, Tainan, 701 Taiwan.
² School of Computing, Graphic Era Hill University, Dehradun, Uttarakhand India.
³ Department of Mathematics, Graphic Era Hill University, Dehradun, Uttarakhand India.
⁴ School of Computer Science, University of Petroleum & Energy Studies, Dehradun, 248007 Uttarakhand India.
⁵ Department of Mathematics, Computer Science & Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand India.
⁶ Institute of Advanced Manufacturing Technologies, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia.

Abstract

Nowadays, advancement in Magnetic Resonance Imaging (MRI) and Computed Tomography Scan (CT-Scan) technologies have defined modern neuroimaging and drastically change the diagnosing of disease in the world healthcare system. These imaging technologies generate NIFTI (Neuroimaging Informatics Technology Initiative) images. Due to COVID-19 last several months CT-Scan has been performed on millions of the CORONA patients, so billions of the NIFTI images have been produced and communicate over the internet for the diagnosing purpose to detect the coronavirus. The communication of these medical images over the internet yielding the major problem of integrity, copyright protection, and other ethical issues for the world health care system. Another critical problem is that; is doctor diagnose the impeccable medical image of the patient because a large amount of COVID-19 patient's data exists. For proper diagnosing it is also necessary to identify impeccable medical image. Therefore, to address these problems a secure and robust watermarking scheme is needed for these images. Various watermarking schemes have been developed for bmp, .jpg, .png, DICOM, and other image formats but the noticeable contribution is not reported for the NIFTI images. In this paper a robust and hybrid watermarking scheme for NIFTI images based on Lifting Wavelet Transform (LWT), MSVD (Multiresolution Singular Value Decomposition) and QR factorization. The combination of LWT, QR, and MSVD helps in retaining the sensitivity of the NIFTI image and improve the robustness of the watermarking scheme. In this scheme, multiple watermarks are inserted across the first slice of the NIFTI image. The proposed watermarking scheme is sustained against various noise attacks and performance is measured in terms of PSNR, SNR, SSIM, Quality of image, and Normalized correlation. Quality of the image is much significant that lie between .99994 to .99998 and SSIM reported from .94 to .99. Whereas the PSNR of the proposed scheme lies between 56.76 to 57.28 db and NC values lie between .9993 to .9998. which shows that the results are better than the existing schemes where PSNR is lies between 32.66 to 52.02 db. Watermarking, NIFTI, MSVD, LWT, QR and Image.

Keywords: LWT; MSVD; NIFTI; QR and Image; Watermarking.