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WoundNetB7-DFU-Analysis
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@@ -22,7 +22,7 @@ End-to-end pipeline for Diabetic Foot Ulcer (DFU) analysis:
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  Input Image (DFU photograph)
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  |
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  v
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- [1] WoundNetB7 Segmentation (EfficientNet-B7 + ASPP + CBAM + TAM)
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  -> 4-class masks: background, foot, perilesion, ulcer
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  -> Ulcer Dice: 0.927 (95% CI: [0.917, 0.936])
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@@ -44,7 +44,7 @@ Input Image (DFU photograph)
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  | Component | Architecture | Metric | Value |
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  |-----------|-------------|--------|-------|
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- | Segmentation | EfficientNet-B7 + UNet + ASPP + CBAM + TAM | Ulcer Dice | 0.927 |
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  | PWAT Item 7 | XGBoost + SMOTE | MAE / Adjacent | 0.61 / 89.3% |
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  | Fitzpatrick | ITA calibrated thresholds | Exact match | 86.9% |
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  Input Image (DFU photograph)
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  |
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  v
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+ [1] WoundNetB7 Segmentation (EfficientNet-B7 + ASPP + CBAM)
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  -> 4-class masks: background, foot, perilesion, ulcer
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  -> Ulcer Dice: 0.927 (95% CI: [0.917, 0.936])
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  |
 
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  | Component | Architecture | Metric | Value |
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  |-----------|-------------|--------|-------|
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+ | Segmentation | EfficientNet-B7 + UNet + ASPP + CBAM | Ulcer Dice | 0.927 |
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  | PWAT Item 7 | XGBoost + SMOTE | MAE / Adjacent | 0.61 / 89.3% |
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  | Fitzpatrick | ITA calibrated thresholds | Exact match | 86.9% |
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