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| title: DermaScan AI | |
| emoji: π¬ | |
| colorFrom: indigo | |
| colorTo: purple | |
| sdk: streamlit | |
| sdk_version: "1.44.1" | |
| python_version: "3.11" | |
| app_file: dermascan_app.py | |
| pinned: false | |
| # DermaScan AI β Clinical Skin Lesion Analysis | |
| Upload a dermoscopy image for **full clinical ABCDE analysis**, risk scoring, | |
| measurements, Grad-CAM explainability, and a downloadable report β all powered | |
| by a trained **U-Net** (ISIC 2018, Dice 0.854). | |
| ## Features | |
| | Feature | Description | | |
| |---|---| | |
| | π― Segmentation | U-Net binary mask with green overlay | | |
| | π¬ ABCDE Analysis | Asymmetry, Border, Color, Diameter β all computed from the mask | | |
| | π Risk Score | Weighted 0β10 gauge with LOW / MEDIUM / HIGH level | | |
| | π Measurements | Area (mmΒ²), Perimeter, Coverage, Bounding box | | |
| | π§ Grad-CAM | Model explainability heatmap | | |
| | π Evolution | Upload a previous scan to track lesion growth | | |
| | π Report | Downloadable PDF + text clinical report | | |
| ## Model | |
| - Architecture: **U-Net** with skip connections | |
| - Dataset: **ISIC 2018 Task 1** (568 images, 70/15/15 split) | |
| - Loss: **BCE + Dice** (50/50) | |
| - Test Dice: **0.8543 Β± 0.0821** | |
| - Weights hosted at: `pavanpraneeth/isic-unet` | |
| > β οΈ **Disclaimer:** DermaScan AI is a research/screening tool only. | |
| > It does NOT constitute a medical diagnosis. Always consult a qualified dermatologist. | |