## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Computation Time (s)** & **Bicubic** & **SRCNN** & **MSDEPC** \\ \hline GPU (Titan Xp) & \textless{}0.01 & 0.21 & 0.29 \\ CPU (Intel Xeon) & \textless{}0.01 & 12.42 & 15.49 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of the computation times of the three algorithms. Figure 2: Images derived from applying algorithms to ultrasound images acquired using the Field 2 program. When algorithms that can improve spatial resolution compared to low-resolution images were applied, visually clear areas were observed, and the proposed MSDEPC showed the best characteristics. The yellow line was used to obtain the intensity profile. MSDEPC algorithm was derived as a noteworthy solution. Our findings demonstrate that the SSIM value of the simulated ultrasound image using the MSDEPC algorithm improved by approximately 38.84% compared to LR. Figures 5-9 show the results of applying the spatial resolution improvement methods to clinical ultrasound images obtained from open sources. Figures 5-9 show images of the carotid artery, a liver hemangiioma, breast malignancy, a thyroid carcinoma, and obstetric much translucency, respectively. By restoring all the clinical ultrasound images using the proposed MSDEPC algorithm, we confirmed that the spatial resolution of the images was visually improved. Figure 3: Graph showing (**a**) intensity profile and (**b**) sigma and (FWHM) values calculated from low-resolution (LR) images and images acquired by applying each spatial resolution improvement algorithm. When using the proposed MSDEPC algorithm, the intensity profile was observed to be the sharpest, and the best FWHM result were also obtained. Figure 4: Graph showing (**a**) peak signal-to-noise ratio (PSNR) and (**b**) structural similarity index metric (SSIM) values calculated from simulated LR images and images acquired by applying each spatial resolution improvement algorithm. The best PSNR and SSIM values were obtained when using the proposed MSDEPC algorithm. Figure 5: Results of applying various spatial-resolution enhancement algorithms to clinical ultrasound images of the carotid artery (The red box area indicates the magnified area). A clear improvement in spatial resolution was observed when using the MSDEPC algorithm at the edge of the blood vessel wall (yellow arrow area). Figure 10a,b show the PSNR and SSIM results, respectively, with respect to the application of various spatial resolution improvement algorithms to clinical ultrasound images. When the LR, bicubic, SRCNN, and proposed MSDEPC algorithms were used, the values were 19.45, 27.23, 36.14, and 45.00, respectively. In addition, the average SSIM values for the clinical ultrasound images obtained using the LR, bicubic, SRCNN, and proposed MSDEPC algorithms were 0.480, 0.592, 0.843, and 0.904, respectively. The same tendencies as those of the PSNR and SSIM values derived from the simulation study were observed, and we proved that the best quantitative spatial resolution values were obtained using the MSDEPC algorithm. In particular, we confirmed that the PSNR and SSIM values of the clinical ultrasound images improved by approximately 2.33 times and 88.58%, respectively, using the MSDEPC algorithm compared to LR. Figure 6: Results of applying various spatial resolution enhancement algorithms to clinical ultrasound images of a liver hemangiioma (The red box area indicates the magnified area). When using the proposed MSDEPC algorithm, the margin of the liver hemangiioma ultrasound image was clearly observable (yellow arrow area). Figure 7: Results of applying various spatial resolution enhancement algorithms to clinical breast malignancy ultrasound images (The red box area indicates the magnified area). When using the proposed MSDEPC algorithm, it was confirmed that irregular parts of the malignancy area could be clearly derived (yellow arrow area). In ultrasound images of carotid arteries, intima-media thickness is often measured, and a thickness of less than 0.8 mm is diagnosed as normal.