Research map / 3D vision / 3D generation
Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add long residual connections (ablation) | volumetric ConvNet with short residual connections · PROMISE12 10-fold CV | Dice: 84.68 -> 86.93 | Helped |
| add short residual connections (ablation) | volumetric ConvNet with long residual connections · PROMISE12 10-fold CV | Dice: 84.38 -> 86.93 | Helped |
| add mixed long and short residual connections (ablation) | volumetric ConvNet without residual connections · PROMISE12 10-fold CV | Dice: 81.63 -> 86.93 | Helped |
| add mixed residual connections (ablation) | volumetric ConvNet · PROMISE12 10-fold CV | validation loss / convergence | Helped |
| use 3D ConvNet with mixed residual connections and deep supervision | prostate segmentation · PROMISE12 test | challenge score: 84.36 -> 86.65 | Helped |
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