This project is an image classification system designed to detect brain tumors from MRI scan images using Convolutional Neural Networks (CNNs).
It aims to assist radiologists and medical professionals by providing quick and reliable tumor detection results.
The goal of this project is to build and train a deep learning model that can accurately distinguish between tumorous and non-tumorous brain MRI scans.
It uses Python and TensorFlow/Keras for the CNN model, with a simple Flask web application interface to upload and predict MRI images.
- 🧠 Automatic Brain Tumor Detection from MRI scans
- 🖼️ Image Preprocessing: resizing, normalization, and augmentation
- 🤖 Deep Learning Model built using CNN architecture
- 💾 Dataset Handling for training and testing
- 🌐 Web Interface for real-time predictions
- 📊 Accuracy Evaluation with graphs (loss and accuracy curves)
| Category | Technology |
|---|---|
| Language | Python |
| Deep Learning | TensorFlow, Keras |
| Data Processing | NumPy, Pandas |
| Visualization | Matplotlib, Seaborn |
| Image Handling | OpenCV, PIL |
| Web Framework | Flask |
| Dataset | Brain MRI Images (Kaggle or custom dataset) |
git clone https://github.com/<your-username>/Brain-Tumor-Detection.git
cd Brain-Tumor-Detection