# Secure NIfTI Image Authentication Scheme for Modern Healthcare System
## 4 Proposed Watermarking Method
### Watermark Extraction Process
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Slices of NIfTI Image** & **NC** & **Q** & **PSNR** & **SSIM** & **Extracted Watermark** \\ \hline Slc1 & 0.9997 & 0.9996 & 54.31 & 0.9894 & **NCKU** \\  & & & & & \\ Slc2 & 0.9994 & 0.9995 & 53.82 & 0.9947 & **CSIE** \\  & & & & & \\ Slc3 & 1 & 0.9999 & 53.96 & 0.9912 & **NCKU** \\  & & & & & \\ Slc4 & 0.9989 & 0.9991 & 53.75 & 0.9928 & **CSIE** \\  & & & & & \\ Slc5 & 1 & 0.9999 & 54.16 & 0.9899 & **NCKU** \\  & & & & & \\ Slc6 & 0.9996 & 0.9993 & 53.21 & 0.9965 & **CSIE** \\  & & & & & \\ Slc7 & 1 & 0.9998 & 53.86 & 0.9936 & **NCKU** \\  & & & & & \\ Slc8 & 1 & 0.9997 & 54.21 & 0.9898 & **CSIE** \\  & & & & & \\ Slc9 & 0.9997 & 0.9990 & 53.67 & 0.9890 & **CSIE** \\  & & & & & \\ Slc10 & 1 & 0.9998 & 53.88 & 0.9939 & **CSIE** \\  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Major quality metrics of the proposed watermarking scheme. Once the watermark has been appropriately extracted from the supplied NIfTI image, radiologists or other medical practitioners are responsible for ensuring that they diagnose the ideal medical image. It is a question of life and death for the sufferer. A patient's unique ID and name might be included as a watermark in the form of a logo or image. Thus, we believe that our technique will play a critical role in verifying NIfTI images. Figure 7 shows the significant parameters of the generated watermarked image in the proposed scheme. We depict the NC, Q, PSNR, and SSIM of the watermarked slice in Figure 7. The proposed scheme's results are promising, where SSIM, Q, and NC of the proposed approach are near one, and the PSNR is around 54 db. The proposed scheme is also evaluated with the different sizes of watermark embedding. For the experiment, we embedded the watermark at sizes of \(64\times 64\), \(128\times 128\), and \(256\times 256\) in the slice. Figure 8 displays the watermarked slice and the \(256\times 256\) watermark recovered from the particular slice, where the PSNR of the watermarked image

Figure 7: NC, Q, PSNR, and SSIM of the watermarked slice in the proposed watermarking scheme. is 47.12 db and the SSIM is 0.9822. Figure 8b shows the watermarked slice as well as the extracted watermark at a size of \(128\times 128\), where the PSNR is 53.67 and the SSIM is 0.989. Figure 8c shows the watermarked slice and extracted watermark at a size of \(64\times 64\), where the PSNR is 59.34 and the SSIM is 0.9988. If the large-scale watermark is embedded, it degrades the quality of the watermarked slice. Thus, it is essential to utilize a small-sized watermark for medical image authentication purposes. ### Comparison with Existing Schemes

In this part, the performance of the proposed approach is compared to that of current watermarking methods. Based on these comparisons, it is clear that the proposed approach was highly successful in producing a watermarked image of good quality. Furthermore, the comparison is carried out by inserting a \(128\times 128\)-pixel watermark into a \(630\times 630\)-pixel NIFTI image slice. The results of our suggested methodology are compared in Table 2 with the results of other techniques that are currently accessible. The comparison reveals that the results obtained using our procedure were far more substantial than those obtained using existing strategies. As shown in Table 2, in terms of PSNR, our technique outperformed the methods of [PERSON] et al. [1], [PERSON] et al. [2], [PERSON] et al. [17], [PERSON] et al. [21], [PERSON] et al. [24], [PERSON] et al. [25], and [PERSON] et al. [26] and also showed significant PSNRs. Our approach's SSIM is closer to one than other existing techniques, demonstrating the improved quality of the watermarked slice produced by our methodology. Figure 9 visually represents an NC comparison between the proposed system and three other current methods. viz. [PERSON] et al. [1], [PERSON] et al. [2], and [PERSON] et al. [17]. In some cases, our method approaches the maximum normalized correlation. In some cases, however, it is closer to the benchmark.