## 3 Results
### Head Dataset Results
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & \(99.83\)\(\pm\) 8.06 & 24.83 \(\pm\) 0.613 & 0.931 \(\pm\) 0.009 \\ \hline
**3D-32** & \(104.57\)\(\pm\) 8.40 & 24.52 \(\pm\) 0.681 & 0.925 \(\pm\) 0.013 \\ \hline
**3D-16 av** & \(97.88\)\(\pm\) 7.84 & **25.15 \(\pm\) 0.626** & **0.935 \(\pm\) 0.009** \\ \hline
**3D-16** & \(98.14\)\(\pm\) 7.99 & 24.69 \(\pm\) 1.280 & 0.927 \(\pm\) 0.025 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Head dataset with Residual-Net. Mean Absolute Error, PSNR and Pearson coefficient on the head data set obtained using Residual net with different convolutions and reconstructions. Figure 7: Head results using 3D-16 networks. \begin{table}
\begin{tabular}{c c c c} \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & 352.15 \(\pm\) 19.96 & 18.58 \(\pm\) 0.441 & 0.811 \(\pm\) 0.014 \\ \hline
**3D-32** & 358.74 \(\pm\) 15.96 & 18.39 \(\pm\) 0.385 & 0.798 \(\pm\) 0.017 \\ \hline
**3D-16 av** & 338.81 \(\pm\) 17.81 & 18.86 \(\pm\) 0.410 & 0.816 \(\pm\) 0.016 \\ \hline
**3D-16** & **336.32 \(\pm\) 15.35** & **18.93 \(\pm\) 0.359** & **0.821 \(\pm\) 0.015** \\ \hline \end{tabular}
\end{table} 
Table 6: Head dataset Bone with Residual-Net. Mean Absolute Error, PSNR and Pearson coefficient within the bone on the head data set obtained using Residual net with different convolutions and reconstructions. \begin{table}
\begin{tabular}{c c c c} \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & 186.28 \(\pm\) 23.86 & 21.17 \(\pm\) 1.51 & 0.544 \(\pm\) 0.075 \\ \hline
**3D-32** & 160.85 \(\pm\) 28.58 & 23.38 \(\pm\) 1.47 & 0.685 \(\pm\) 0.079 \\ \hline
**3D-16 av** & **153.23 \(\pm\) 31.25** & 23.51 \(\pm\) 1.67 & **0.695 \(\pm\) 0.083** \\ \hline
**3D-16** & 153.31 \(\pm\) 29.41 & **23.54 \(\pm\) 1.559** & 0.694 \(\pm\) 0.079 \\ \hline \end{tabular}
\end{table} 
Table 7: Head dataset Fat with U-net. Mean Absolute Error, PSNR and Pearson coefficient within the fat on the head data set obtained using U-net with different convolutions and reconstructions. \begin{table}
\begin{tabular}{c c c c} \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & 382.64 \(\pm\) 23.85 & 17.48 \(\pm\) 0.577 & 0.757 \(\pm\) 0.021 \\ \hline
**3D-32** & 326.33 \(\pm\) 15.47 & 19.71 \(\pm\) 0.362 & 0.849 \(\pm\) 0.014 \\ \hline
**3D-16 av** & 289.64 \(\pm\) 15.57 & **20.08 \(\pm\) 0.382** & 0.860 \(\pm\) 0.013 \\ \hline
**3D-16** & **289.10 \(\pm\) 15.64** & 20.05 \(\pm\) 0.384 & **0.861 \(\pm\) 0.013** \\ \hline \end{tabular}
\end{table} 
Table 4: Head dataset Bone with U-net. Mean Absolute Error, PSNR and Pearson coefficient within the bone on the head data set obtained using U-net with different convolutions and reconstructions. \begin{table}
\begin{tabular}{c c c c} \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & 352.15 \(\pm\) 19.96 & 18.58 \(\pm\) 0.441 & 0.811 \(\pm\) 0.014 \\ \hline
**3D-32** & 358.74 \(\pm\) 15.96 & 18.39 \(\pm\) 0.385 & 0.798 \(\pm\) 0.017 \\ \hline
**3D-16 av** & 338.81 \(\pm\) 17.81 & 18.86 \(\pm\) 0.410 & 0.816 \(\pm\) 0.016 \\ \hline
**3D-16** & **336.32 \(\pm\) 15.35** & **18.93 \(\pm\) 0.359** & **0.821 \(\pm\) 0.015** \\ \hline \end{tabular}
\end{table} 
Table 5: Head dataset Bone with Atrous-Net. Mean Absolute Error, PSNR and Pearson coefficient within the bone on the head data set obtained using Atrous net with different convolutions and reconstructions. \begin{table}
\begin{tabular}{c c c c} \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & \(157.11\pm 24.30\) & \(22.85\pm 1.59\) & 0.662 \(\pm\) 0.078 \\ \hline
**3D-32** & \(168.65\pm 24.25\) & \(22.35\pm 1.432\) & 0.646 \(\pm\) 0.072 \\ \hline
**3D-16 av** & \(158.88\pm 25.08\) & \(\mathbf{22.94\pm 1.539}\) & **0.666 \(\pm\) 0.075** \\ \hline
**3D-16** & \(159.20\pm 24.66\) & \(22.72\pm 1.404\) & 0.659 \(\pm\) 0.069 \\ \hline \end{tabular}
\end{table} 
Table 10: Head dataset Soft-tissue with U-net.