A full-stack AI-powered web application for brain tumor detection using MRI scans. The system uses deep learning (VGG16), real-time image processing, dynamic PDF report generation, and a searchable scan history — all packaged in a responsive UI.
Seamlessly upload MRI scans from your system.
Scans are analyzed using a fine-tuned VGG16 CNN model to classify tumor types.
Generate a structured, color-coded PDF report containing:
- Tumor prediction & confidence
- Patient and hospital metadata
- QR verification
- Medical disclaimer
Search previous MRI reports using the patient name. History is stored locally via JSON.
Modern UI with toggleable dark theme for better readability.
Click the thumbnail above to watch a full walkthrough of:
- Uploading MRI Scans
- AI-based Tumor Detection
- PDF Report Generation
- Scan Search Functionality
- Dark Mode UI Preview
- Frontend: HTML, CSS (Bootstrap), JavaScript
- Backend: Flask (Python)
- AI Model: VGG16 (TensorFlow/Keras)
- Visualization: FPDF (for PDF), PIL, QRCode
- Data Storage: Local JSON (scan history)
Brain-Tumor-Detection/ │ ├── models/ # Saved .keras model ├── templates/ # HTML templates (Flask) ├── static/ # Static assets (if any) ├── screens/ # Screenshots & video preview ├── uploads/ # Uploaded images ├── reports/ # Generated PDFs ├── main.py # Flask App └── README.md
This project is open-source under the MIT License.
Developed with ❤️ by Nipurn Goyal