WoundNetB7 — DFU Analysis Pipeline
EfficientNet-B7 + ASPP + CBAM + CoordAttention + TAM • Ulcer Dice: 0.927
Pipeline: the image goes through 4 sequential stages.
Model: WoundNetB7 with Combo Loss + Small Object Loss. Attention modules: CBAM, CoordAttention, TAM (fractal + Euler).
TTA: 6-fold test-time augmentation.
Model: WoundNetB7 with Combo Loss + Small Object Loss. Attention modules: CBAM, CoordAttention, TAM (fractal + Euler).
TTA: 6-fold test-time augmentation.
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Integrated Clinical Assessment Report
Single-page summary combining segmentation, Fitzpatrick / ITA estimation and Fitzpatrick-adjusted PWAT scoring. Designed for clinical staff.
1
Binary Ulcer Segmentation
2
Multi-Class Segmentation (4 classes)
Class legend:
Foot — healthy tissue
Perilesional — periulcer area
Ulcer — wound bed
3
Fitzpatrick / ITA Skin Type Estimation
4
PWAT — Raw vs Fitzpatrick-Adjusted Scores
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Download Clinical Report
Generates a PDF report with all visualizations and structured data. Run an analysis first.
Guided Capture for Clinical Staff
Use the device camera to capture an image of the diabetic foot. The green silhouette guides correct foot positioning for optimal analysis.
Instructions for clinical staff:
1. Plantar surface facing the camera
2. Distance: 30-40 cm from the lens
3. Uniform lighting, no shadows
4. Neutral background (white/blue sheet)
5. Include the full ulcer + surrounding healthy skin
6. Avoid direct flash (causes glare)
7. Keep the device steady
8. Clean the lens before capturing
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Integrated Clinical Assessment Report
1
Segmentation Result
2
Fitzpatrick + PWAT
WoundNetB7 • Doctoral Thesis • Marcelo Marquez-Murillo •
Ulcer Dice 0.927 (95% CI: [0.917, 0.936]) •
Debiasing: 46.6% max group gap reduction (p < 10-55)