## 6 Discussion
\begin{table}
\begin{tabular}{l c c c c c} \hline
**SRR Procedure** & **N** & **M** & **SD** & **t** & \(\mathbf{p}\)** \\ \hline SR-no, MC-no & 100 & 29.89 & 0.01 & 1.254 & 0.121 \\ \hline SR-no, MC-yes & 100 & 26.32 & 0.01 & 0.622 & 0.513 \\ \hline cubic spline, MC-yes & 100 & 23.45 & 0.01 & 0.143 & 0.283 \\ \hline [PERSON] [50] & 100 & 16.41 & 0.01 & \(-\)0.324 & 0.432 \\ \hline [PERSON] [20] & 100 & 16.44 & 0.01 & \(-\)0.354 & 0.443 \\ \hline [PERSON] [51] & 100 & 16.31 & 0.01 & \(-\)0.461 & 0.336 \\ \hline [PERSON] no. 2 [43] & 100 & 15.26 & 0.01 & \(-\)0.511 & 0.551 \\ \hline [PERSON] et al. [52] & 100 & 15.21 & 0.03 & \(-\)0.238 & 0.744 \\ \hline [PERSON] et al. [53] & 100 & 14.31 & 0.04 & \(-\)0.013 & 0.232 \\ \hline [PERSON] et al. [54] & 100 & 15.81 & 0.01 & 0.542 & 0.543 \\ \hline [PERSON] et al. [55] & 100 & 19.01 & 0.03 & \(-\)1.002 & 0.444 \\ \hline [PERSON] et al. [17] & 100 & 15.03 & 0.02 & \(-\)0.886 & 0.128 \\ \hline The presented algorithm & 100 & 14.03 & 0.01 & \(-\)1.002 & 0.553 \\ \hline \end{tabular}
\end{table} 
Table 4: The statistical data regarding the Mean Absolute Error (MAE) metrics for Figure 8 are presented. \begin{table}
\begin{tabular}{l c c c c} \hline
**SRR Procedure** & **N** & **M** & **SD** & **t** & \(\mathbf{p}\)** \\ \hline SR-no, MC-no & 100 & 20.16 & 0.01 & 1.091 & 0.273 \\ \hline SR-no, MC-yes & 100 & 24.21 & 0.01 & \(-\)0.739 & 0.438 \\ \hline cubic spline, MC-yes & 100 & 23.21 & 0.01 & 0.181 & 0.271 \\ \hline [PERSON] [50] & 100 & 26.36 & 0.01 & \(-\)0.311 & 0.431 \\ \hline [PERSON] [20] & 100 & 29.11 & 0.01 & \(-\)0.363 & 0.411 \\ \hline [PERSON] [51] & 100 & 28.71 & 0.01 & \(-\)0.411 & 0.437 \\ \hline [PERSON] no. 2 [43] & 100 & 29.75 & 0.01 & \(-\)0.521 & 0.514 \\ \hline [PERSON] et al. [52] & 100 & 30.03 & 0.04 & \(-\)0.339 & 0.612 \\ \hline [PERSON] et al. [53] & 100 & 30.00 & 0.03 & \(-\)0.063 & 0.531 \\ \hline [PERSON] et al. [54] & 100 & 29.71 & 0.02 & 0.443 & 0.625 \\ \hline [PERSON] et al. [55] & 100 & 31.41 & 0.05 & \(-\)1.101 & 0.341 \\ \hline [PERSON] et al. [17] & 100 & 31.66 & 0.01 & \(-\)0.931 & 0.368 \\ \hline The proposed algorithm & 100 & 32.99 & 0.01 & \(-\)0.568 & 0.358 \\ \hline \end{tabular}
\end{table} 
Table 3: The statistical data regarding the Peak Signal-to-Noise Ratio (PSNR) metrics for the image depicted in Figure 8 are provided in this document. The word “M values” refers to the mean value of the calculated Peak Signal-to-Noise Ratios (PSNRs). \begin{table}
\begin{tabular}{l c c c c c} \hline \multicolumn{2}{c}{**The Trajectory Used for Sampling in k-Space**} & **N** & **M** & **SD** & **t(99)** & \(p\)** \\ \hline The unaltered multi-blade k-space sampling technique & 100 & 29.81 & 0.01 & \(-\)1.882 & 0.061 \\ \hline The proposed algorithm & 100 & 32.99 & 0.00 & 1.149 & 0.253 \\ \hline \end{tabular}
\end{table} 
Table 6: The statistical data regarding the Peak Signal-to-Noise Ratio (PSNR) for the Figure 8. The symbol M represents the average value of the observed Peak Signal-to-Noise Ratios (PSNRs). \begin{table}
\begin{tabular}{l c c c c c} \hline \multicolumn{2}{c}{**The Trajectory Used for Sampling in k-Space**} & **N** & **M** & **SD** & **t(99)** & \(p\)** \\ \hline The unaltered multi-blade k-space sampling technique & 100 & 18.12 & 0.01 & \(-\)1.881 & 0.053 \\ \hline The proposed algorithm & 100 & 13.19 & 0.00 & 1.149 & 0.223 \\ \hline \end{tabular}
\end{table} 
Table 7: The statistical data regarding the Mean Absolute Error (MAE) metrics for Figure 8 are presented. \begin{table}
\begin{tabular}{l c c c c} \hline \multicolumn{2}{c}{**The Trajectory Used for Sampling in k-Space**} & **N** & **M** & **SD** & **t(99)** & \(p\)** \\ \hline The unaltered multi-blade k-space sampling technique & 100 & 2.04 & 0.01 & 0.139 & 0.869 \\ \hline The proposed algorithm & 100 & 4.34 & 0.00 & \(-\)1.268 & 0.262 \\ \hline \end{tabular}
\end{table} 
Table 8: The statistical data regarding the IEM measures for Figure 8 are shown.