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DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation

CVPR 2016 · Detection and segmentation › CNN features · approach: Context modeling for semantic segmentation · 560 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add contour-aware output fusion to multi-level contextual segmentation (ablation)DCAN · Warwick-QU Part AF1: 0.8680 -> 0.9116Helped
Add contour-aware output fusion to multi-level contextual segmentation (ablation)DCAN · Warwick-QU Part BF1: 0.7692 -> 0.7158Hurt
Add contour-aware output fusion to multi-level contextual segmentation (ablation)DCAN · Warwick-QU Part Aobject-level Dice: 0.8666 -> 0.8974Helped
Add contour-aware output fusion to multi-level contextual segmentation (ablation)DCAN · Warwick-QU Part Bobject-level Dice: 0.8001 -> 0.7810Hurt
Add contour-aware output fusion to multi-level contextual segmentation (ablation)DCAN · Warwick-QU Part Aobject-level Hausdorff distance: 74.5955 -> 45.4182Helped
Add contour-aware output fusion to multi-level contextual segmentation (ablation)DCAN · Warwick-QU Part Bobject-level Hausdorff distance: 153.6457 -> 160.3469Hurt

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