isic-segmentation / README.md
Pavan Praneeth
feat: DermaScan AI - full clinical analysis app
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---
title: DermaScan AI
emoji: πŸ”¬
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 |
|---|---|
| 🎯 Segmentation | U-Net binary mask with green overlay |
| πŸ”¬ ABCDE Analysis | Asymmetry, Border, Color, Diameter β€” all computed from the mask |
| πŸ“Š Risk Score | Weighted 0–10 gauge with LOW / MEDIUM / HIGH level |
| πŸ“ Measurements | Area (mmΒ²), Perimeter, Coverage, Bounding box |
| 🧠 Grad-CAM | Model explainability heatmap |
| πŸ“… Evolution | Upload a previous scan to track lesion growth |
| πŸ“„ 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`
> ⚠️ **Disclaimer:** DermaScan AI is a research/screening tool only.
> It does NOT constitute a medical diagnosis. Always consult a qualified dermatologist.