Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/armanx200/brain-tumor-detector
🧠 A deep learning model that classifies brain images as either having a tumor or not.
https://github.com/armanx200/brain-tumor-detector
arman-kianian cnns convolutional-neural-networks deep-learning healthcare-technology image-classification keras medical-ai medical-imaging opencv python tensorflow
Last synced: 11 days ago
JSON representation
🧠 A deep learning model that classifies brain images as either having a tumor or not.
- Host: GitHub
- URL: https://github.com/armanx200/brain-tumor-detector
- Owner: Armanx200
- Created: 2024-05-31T08:29:19.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-05-31T09:50:37.000Z (8 months ago)
- Last Synced: 2024-11-24T09:16:34.603Z (2 months ago)
- Topics: arman-kianian, cnns, convolutional-neural-networks, deep-learning, healthcare-technology, image-classification, keras, medical-ai, medical-imaging, opencv, python, tensorflow
- Language: Python
- Homepage: https://github.com/Armanx200
- Size: 13.4 MB
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
```markdown
# 🧠 Brain Tumor Detection with Deep Learning
Welcome to the **Brain Tumor Detection** project! This repository contains a deep learning model that classifies brain images as either having a tumor or not. Dive into the power of convolutional neural networks (CNNs) and see how they can be used in medical imaging! 🚀
## 📁 Project Structure
```plaintext
brain-tumor-detection/
│
├── brain_tumor_dataset/
│ ├── no/ # Images without tumors
│ └── yes/ # Images with tumors
│
├── Brain-tumor-detector.py # Model training and evaluation
└── Brain-tumor-probability.py # Tumor probability prediction for a specific image
```
## 📜 Description
This project uses a CNN model to classify brain images into two categories:
- **No tumor** (stored in `brain_tumor_dataset/no`)
- **Tumor** (stored in `brain_tumor_dataset/yes`)
### 🛠️ Getting Started
1. **Clone the repository**:
```bash
git clone https://github.com/Armanx200/Brain-tumor-detector.git
cd Brain-tumor-detector
```
2. **Install dependencies**:
```bash
pip install tensorflow opencv-python scikit-learn
```
3. **Download the dataset**:
- Ensure you have the brain tumor dataset in the correct structure as shown above.
### 🚀 Training the Model
Run the `Brain-tumor-detector.py` script to train the model:
```bash
python Brain-tumor-detector.py
```
This script:
- Loads and preprocesses the dataset.
- Splits the data into training and testing sets.
- Builds and trains a CNN model.
- Evaluates the model and displays the test accuracy.
### 🔍 Predicting Tumor Probability
To predict the probability of a specific image having a tumor, use the `Brain-tumor-probability.py` script:
1. Ensure the model is trained and saved as `brain_tumor_model.h5`.
2. Run the prediction script:
```bash
python Brain-tumor-probability.py
```
This script will:
- Load the trained model.
- Preprocess the specified image.
- Output the probability of the image being a tumor.
## 📊 Model Performance
The model achieves impressive accuracy on the test set. See the script output for detailed performance metrics.
## 🛠️ Tools and Technologies
- **TensorFlow/Keras**: For building and training the neural network.
- **OpenCV**: For image processing.
- **Scikit-learn**: For data splitting and preprocessing.
## 📸 Sample Results
Below is an example of how the model predicts the probability of an image being a tumor:
```
Probability of the image being a tumor: 95.44%
```
## 🤝 Contributing
Contributions are welcome! Please create a pull request or open an issue for any improvements or bug fixes.
## 📜 License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
---
*Developed with ❤️ by [Armanx200](https://github.com/Armanx200)*
```