## 3 Results
### Pelvis Dataset Results
Mean Absolute Error, PSNR and Pearson coefficient from U-net using different convolutions and reconstructions in the Pelvis data set. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & 51.81 \(\pm\) 6.99 & 31.39 \(\pm\) 1.272 & 0.690 \(\pm\) 0.056 \\ \hline
**3D-32** & 51.69 \(\pm\) 7.06 & 31.41 \(\pm\) 1.279 & 0.687 \(\pm\) 0.055 \\ \hline
**3D-16 av** & **50.62 \(\pm\) 6.95** & **31.59 \(\pm\) 1.300** & **0.705 \(\pm\) 0.053** \\ \hline
**3D-16** & 51.37 \(\pm\) 7.49 & 31.48 \(\pm\) 1.350 & 0.691 \(\pm\) 0.065 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Pelvis dataset with Atrous-net. Mean Absolute Error, PSNR and Pearson coefficient from Atrous-net using different convolutions and reconstructions in the Pelvis data set. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & **203.73 \(\pm\) 33.59** & **22.98 \(\pm\) 1.607** & **0.471 \(\pm\) 0.094** \\ \hline
**3D-32** & 214.23 \(\pm\) 32.44 & 22.67 \(\pm\) 1.430 & 0.440 \(\pm\) 0.089 \\ \hline
**3D-16 av** & 209.20 \(\pm\) 32.01 & 22.88 \(\pm\) 1.437 & 0.462 \(\pm\) 0.090 \\ \hline
**3D-16** & 208.90 \(\pm\) 32.73 & 22.79 \(\pm\) 1.503 & 0.446 \(\pm\) 0.092 \\ \hline \hline \end{tabular}
\end{table} 
Table 19: Pelvis dataset Bone with U-net. Mean Absolute Error, PSNR and Pearson coefficient from U-net using different convolutions and reconstructions in the Pelvis data set within the bone. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & 51.41 \(\pm\) 6.81 & 31.55 \(\pm\) 1.323 & 0.703 \(\pm\) 0.050 \\ \hline
**3D-32** & 51.35 \(\pm\) 6.47 & 31.38 \(\pm\) 1.208 & 0.689 \(\pm\) 0.046 \\ \hline
**3D-16 av** & **50.59 \(\pm\) 6.41** & **31.55 \(\pm\) 1.246** & **0.705 \(\pm \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & **201.56 \(\pm\) 31.31** & **23.20 \(\pm\) 1.433** & **0.476 \(\pm\) 0.084** \\ \hline
**3D-32** & 227.98 \(\pm\) 32.49 & 22.29 \(\pm\) 1.296 & 0.426 \(\pm\) 0.082 \\ \hline
**3D-16 av** & 222.40 \(\pm\) 32.61 & 22.48 \(\pm\) 1.329 & 0.453 \(\pm\) 0.083 \\ \hline
**3D-16** & 217.19 \(\pm\) 32.75 & 22.56 \(\pm\) 1.420 & 0.443 \(\pm\) 0.085 \\ \hline \hline \end{tabular}
\end{table} 
Table 22: Pelvis dataset Fat with U-Net. Mean Absolute Error, PSNR and Pearson coefficient from U-net using different convolutions and reconstructions in the Pelvis data set within the fat. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & **55.86 \(\pm\) 23.03** & 31.02 \(\pm\) 2.537 & **0.0108 \(\pm\) 0.149** \\ \hline
**3D-32** & 55.05 \(\pm\) 22.61 & 31.20 \(\pm\) 2.432 & \(-\)0.042 \(\pm\) 0.134 \\ \hline
**3D-16 av** & 54.91 \(\pm\) 22.51 & **31.25 \(\pm\) 2.429** & \(-\)0.035 \(\pm\) 0.145 \\ \hline
**3D-16** & **54.55 \(\pm\) 22.32** & 31.24 \(\pm\) 2.419 & \(-\)0.030 \(\pm\) 0.163 \\ \hline \hline \end{tabular}
\end{table} 
Table 23: Pelvis dataset Fat with Atrous-net. Mean Absolute Error, PSNR and Pearson coefficient from Atrous-net using different convolutions and reconstructions in the Pelvis data set within the fat. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **MAE** & **PSNR** & **Pearson** \\ \hline
**2D** & **210.51 \(\pm\) 31.19** & **22.89 \(\pm\) 1.391** & **0.465 \(\pm\) 0.089** \\ \hline
**3D-32** & 220.55 \(\pm\) 33.40 & 22.53 \(\pm\) 1.371 & 0.419 \(\pm\) 0.082 \\ \hline
**3D-16 av** & 214.21 \(\pm\) 34.11 & 22.72 \(\pm\) 1.446 & 0.445 \(\pm\) 0.084 \\ \hline
**3D-16** & 211.11 \(\pm\) 34.19 & 22.81 \(\pm\) 1.490 & 0.428 \(\pm\) 0.086 \\ \hline \hline \end{tabular}
\end{table} 
Table 20: Pelvis dataset Bone with Atrous-net. Mean Absolute Error, PSNR and Pearson coefficient from Atrous-net using different convolutions and reconstructions in the Pelvis data set within the fat.