FatMapper is a state-of-the-art clinical decision-support tool designed for licensed medical professionals. It utilizes artificial intelligence to provide age-based guidance for facial fat grafting procedures and photographic hollowing analysis.
FatMapper helps surgeons planning lipolifting or facial fat grafting procedures by providing:
- Anatomic Volume Estimation: Statistical guidelines for 16 facial regions based on peer-reviewed "Two-thirds Guidelines."
- JMT Point Analysis: Detailed injection point recommendations across 16 specialized markers.
- AI Hollowing Analysis: Automated detection of facial soft-tissue deficits (Minimal, Moderate, Severe).
- Professional Reporting: Instant generation of Excel and printable reports for clinical records.
- Frontend: React 18, Vite, TypeScript, Tailwind CSS, Lucide Icons.
- Backend: Django 5.0, Django REST Framework, JWT Authentication.
- AI Engine: Python-based statistical models, OpenCV for photographic analysis.
- Database: PostgreSQL (Production) / SQLite (Development).
- Infrastructure: Docker, Nginx, AWS EC2, Terraform, Ansible.
This repository is organized into three main modules for easy maintenance and delivery:
FatMapper/
├── backend/ # Django REST API (Python)
│ ├── ai/ # AI Engines & Statistical Models
│ ├── apps/ # Business logic (Users, Reports, etc.)
│ ├── core/ # Main settings & URL routing
│ └── templates/ # Email & HTML templates
├── frontend/ # React SPA (TypeScript)
│ ├── src/ # Component architecture & Business logic
│ └── public/ # Static assets (icons, legal docs)
├── infra/ # Infrastructure as Code
│ ├── terraform/ # AWS Provisioning scripts
│ └── ansible/ # Server configuration & Docker setup
├── nginx/ # Reverse proxy & SSL configuration
├── docker-compose.prod.yml # Production orchestration
└── README.md # Main project documentation
- Python 3.12+ (Backend)
- Node.js 20+ (Frontend)
- uv (Fast Python package manager)
cd backend
uv sync # Install dependencies
source .venv/bin/activate # Activate environment
python manage.py migrate # Setup database
python manage.py runserver # Start API at http://localhost:8000API Documentation available at: http://localhost:8000/v1/users/auth/docs/
cd frontend
npm install # Install dependencies
npm run dev # Start Dev server at http://localhost:5173The project is fully containerized using Docker. Deployment to AWS is automated via Terraform and Ansible.
docker compose -f docker-compose.prod.yml up -d --buildFor detailed deployment instructions (AWS setup, SSL certificates, CI/CD), please refer to the DEVELOPMENT_GUIDE.md.
FatMapper does not store patient data. All photographic analysis is performed locally within the session.
- Full Terms of Use are integrated into the application registration flow.
- A PDF copy is located at
frontend/public/terms_of_use.pdf.
Developed for clinical excellence. © 2026 FatMapper. All rights reserved.