`ADNI-1`. Both FPSGR methods obtain results comparable with optimization-based LDDMM. This justifies the use of the proposed methods. The correction network generally increases the prediction accuracy over using the prediction network only.

[max width=]{}

  ------------------- --------------------- --------------------- --------------------- --------------------- --------------------- --------------------- --
   `Measured Images`        $I_{6mo}$            $I_{12mo}$            $I_{18mo}$            $I_{24mo}$            $I_{36mo}$            $I_{48mo}$       
       Original        0.0770 $\pm$ 0.0212   0.0764 $\pm$ 0.0207   0.0890 $\pm$ 0.0220   0.0810 $\pm$ 0.0223   0.0899 $\pm$ 0.0341   0.0940 $\pm$ 0.0415  
         LDDMM         0.0750 $\pm$ 0.0194   0.0686 $\pm$ 0.0176   0.0734 $\pm$ 0.0190   0.0609 $\pm$ 0.0168   0.0628 $\pm$ 0.0177   0.0663 $\pm$ 0.0221  
        Pred-1         0.0754 $\pm$ 0.0213   0.0694 $\pm$ 0.0182   0.0742 $\pm$ 0.0195   0.0621 $\pm$ 0.0188   0.0654 $\pm$ 0.0184   0.0698 $\pm$ 0.0238  
      Pred+Corr-1      0.0754 $\pm$ 0.0211   0.0691 $\pm$ 0.0182   0.0734 $\pm$ 0.0192   0.0615 $\pm$ 0.0166   0.0642 $\pm$ 0.0188   0.0688 $\pm$ 0.0235  
  ------------------- --------------------- --------------------- --------------------- --------------------- --------------------- --------------------- --

Bias {#sec:bias}
----

[max width=0.47]{}

                             Slope                     Intercept            \#data
  -- ------------- -------------------------- ---------------------------- --------
           LDDMM-1  \[0.62, **0.70**, 0.78\]   \[-0.25,**-0.08**, 0.09\]   
            Pred-1  \[0.37, **0.44**, 0.50\]   \[-0.21, **-0.08**, 0.05\]  
       Pred+Corr-1  \[0.61, **0.68**, 0.75\]   \[-0.15, **-0.01**, 0.13\]  
           LDDMM-2  \[0.57, **0.66**, 0.75\]   \[-0.21, **-0.04**, 0.14\]  
            Pred-2  \[0.43, **0.50**, 0.57\]   \[-0.16, **-0.02**, 0.11\]  
       Pred+Corr-2  \[0.51, **0.58**, 0.65\]   \[-0.12, **0.01**, 0.15\]   
           LDDMM-1  \[0.72, **0.94**, 1.16\]   \[-0.45, **-0.03**, 0.39\]  
            Pred-1  \[0.39, **0.58**, 0.78\]   \[-0.43, 