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. 2020 Oct 8;20:113. doi: 10.1186/s12880-020-00511-1

Table 1.

Comparison between the segmentation accuracy

Cardiac Chamber Pg-GAN Actual pat. MRI p-value
Percent Variation
Long axis view:
 Left Ventricle 0.021 [0.017–0.027] 0.014 [0.012–0.018] < 0.0001
 Right Ventricle 0.019 [0.016–0.024] 0.016 [0.012–0.022] < 0.0001
 Right Atrium 0.014 [0.011–0.018] 0.011 [0.009–0.014] < 0.0001
Short axis view:
 Left Ventricle 0.013 [0.010–0.019] 0.013 [0.010–0.017] 0.41
 Right Ventricle 0.035 [0.025–0.042] 0.036 [0.028–0.050] 0.003
Dice Metric
Long axis view:
 Left Ventricle 0.978 [0.973–0.983] 0.986 [0.982–0.988] < 0.0001
 Right Ventricle 0.981 [0.976–0.984] 0.984 [0.978–0.988] < 0.0001
 Right Atrium 0.986 [0.983–0.989] 0.989 [0.985–0.991] < 0.0001
Short axis view:
 Left Ventricle 0.987 [0.982–0.991] 0.987 [0.983–0.990] 0.45
 Right Ventricle 0.965 [0.958–0.975] 0.964 [0.951–0.972] 0.002

Comparison between the segmentation accuracy (percent variation and Dice metric) between U-Net based segmentation models trained entirely on synthetic frames generated by the generative adversarial network (PG GAN) and those trained on actual patient magnetic resonance imaging (MRI) frames. p-values were calculated using a paired non-parametric test