🧠 Brain Tumor Detection using Deep Learning

An AI-powered solution to detect and localize brain tumors from MRI scans.

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🧩 Project Overview

This project uses deep learning techniques to detect the presence of brain tumors from MRI images. It provides not only a diagnosis (tumor/no tumor) but also highlights the tumor region in the image if detected. The system is designed to assist radiologists and medical professionals with faster and more accurate results.

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🔬 How It Works

1. User uploads an MRI image through the interface.
2. The image is processed by a pre-trained deep learning model.
3. The model classifies the image as either:
   • No Tumor
   • Tumor Detected
4. If a tumor is found, the system overlays a segmentation mask to show its location.
5. Results are stored in MongoDB for tracking and analysis.

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⚙️ Technologies Used

• Python (Flask backend)
• TensorFlow / Keras – for deep learning model
• OpenCV – image processing
• MongoDB – to store scan results
• Flask – to serve the web interface
• HTML/CSS + Bootstrap – simple frontend

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✅ Features

• 🖼️ Upload MRI scan via web interface
• 🧠 Classifies tumor presence using a CNN model
• 📍 Displays tumor region if detected
• 🗂️ Stores each result with timestamp in MongoDB
• ⚡ Fast, reliable, and easy to use

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📈 Future Scope

• Add support for multiple tumor types (meningioma, glioma, etc.)
• Enhance segmentation accuracy with U-Net or Mask R-CNN
• Add patient management and report generation
• Integrate user authentication and role-based access

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🙌 Contributing

Want to improve the accuracy or UI? We welcome all kinds of contributions!

To contribute:

• Fork this repo
• Create a branch (git checkout -b feature/new-feature)
• Commit your changes
• Open a Pull Request!

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👨‍💻 Made with 💙 by Mohit

Empowering diagnosis with the power of AI.