From: Artifact-free fat-water separation in Dixon MRI using deep learning
Model | Run | Water | Fat | ||
---|---|---|---|---|---|
SSIM | PSNR (dB) | SSIM | PSNR (dB) | ||
\(IP\rightarrow \hat{F},\hat{W}\) | 1 | 0.919Â \({\pm }\)Â 0.011 | 24.28Â \({\pm }\)Â 0.78 | 0.945Â \({\pm }\)Â 0.009 | 24.70Â \({\pm }\)Â 0.84 |
 | 2 | 0.913 \({\pm }\) 0.012 | 24.07 \({\pm }\) 0.70 | 0.942 \({\pm }\) 0.008 | 24.45 \({\pm }\) 0.75 |
 | 3 | 0.926 \({\pm }\) 0.009 | 24.74 \({\pm }\) 0.77 | 0.942 \({\pm }\) 0.008 | 25.07 \({\pm }\) 0.83 |
 | 4 | 0.919 \({\pm }\) 0.010 | 24.35 \({\pm }\) 0.74 | 0.945 \({\pm }\) 0.010 | 24.55 \({\pm }\) 0.81 |
\(IP,OP\rightarrow \hat{F},\hat{W}\) | 1 | 0.961Â \({\pm }\)Â 0.006 | 28.99Â \({\pm }\)Â 0.91 | 0.975Â \({\pm }\)Â 0.004 | 29.67Â \({\pm }\)Â 0.96 |
 | 2 | 0.962 \({\pm }\) 0.005 | 28.94 \({\pm }\) 0.82 | 0.972 \({\pm }\) 0.003 | 29.00 \({\pm }\) 0.80 |
 | 3 | 0.966 \({\pm }\) 0.005 | 29.41 \({\pm }\) 0.83 | 0.976 \({\pm }\) 0.004 | 29.58 \({\pm }\) 0.85 |
 | 4 | 0.963 \({\pm }\) 0.005 | 29.10 \({\pm }\) 0.84 | 0.974 \({\pm }\) 0.004 | 29.41 \({\pm }\) 0.83 |
\(IP,OP\rightarrow \hat{F},\hat{W}\) | 1 | 0.930Â \({\pm }\)Â 0.010 | 25.11Â \({\pm }\)Â 0.83 | 0.953Â \({\pm }\)Â 0.007 | 25.37Â \({\pm }\)Â 0.91 |
(Dixon generator loss) | 2 | 0.928Â \({\pm }\)Â 0.008 | 25.51Â \({\pm }\)Â 0.85 | 0.949Â \({\pm }\)Â 0.007 | 25.51Â \({\pm }\)Â 0.85 |
 | 3 | 0.935 \({\pm }\) 0.009 | 25.94 \({\pm }\) 0.91 | 0.952 \({\pm }\) 0.008 | 26.14 \({\pm }\) 0.96 |
 | 4 | 0.924 \({\pm }\) 0.009 | 25.36 \({\pm }\) 0.89 | 0.951 \({\pm }\) 0.008 | 25.35 \({\pm }\) 0.88 |