https://github.com/haybnzz/neurotumornet
A deep learning model for brain tumor classification using MRI images.
https://github.com/haybnzz/neurotumornet
ai cnn-classification model mri-images python
Last synced: about 2 months ago
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A deep learning model for brain tumor classification using MRI images.
- Host: GitHub
- URL: https://github.com/haybnzz/neurotumornet
- Owner: haybnzz
- License: other
- Created: 2025-03-20T17:02:42.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-03-20T20:08:04.000Z (about 2 months ago)
- Last Synced: 2025-03-20T20:08:41.196Z (about 2 months ago)
- Topics: ai, cnn-classification, model, mri-images, python
- Language: Python
- Homepage: https://haybnz.glitch.me
- Size: 258 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# NeuroTumorNet
A deep learning model for brain tumor classification using MRI images.
[](https://github.com/haybnzz/NeuroTumorNet) [](https://github.com/haybnzz/NeuroTumorNet/blob/main/LICENSE) [](https://huggingface.co/haydenbanz/NeuroTumorNet/resolve/main/brain_tumor_model.h5?download=true) [](https://huggingface.co/spaces/haydenbanz/NeuroTumorNets) [](https://huggingface.co/datasets/haydenbanz/TumorVisionDatasets/tree/main) [](https://github.com/haybnzz/NeuroTumorNet/issues) [](https://github.com/haybnzz/NeuroTumorNet/stargazers)  [](https://haybnz.glitch.me/) [](https://www.kaggle.com/models/haydenbanz/neurotumornet) [](blob:https://github.com/eaddddc7-df41-49f0-9658-15a716ec46de)
## Description
🧠 Classify brain tumors with **NeuroTumorNet**! 🩻 Powered by a CNN built with TensorFlow 🤖, this tool analyzes MRI scans to detect Glioma, Meningioma, Pituitary, or No Tumor. 🚀 Upload an image via the Streamlit UI 🌐 and get instant predictions with confidence scores! ✨ Download the model or explore the live demo and datasets below. 🖥️
## Overview
NeuroTumorNet is a CNN-based tool that classifies brain MRI images into four categories:
- Glioma tumor
- Meningioma tumor
- No tumor
- Pituitary tumor
The model uses a convolutional neural network architecture built with TensorFlow and Keras to provide accurate tumor classification.
## 🔍 Features
- Automatic detection and classification of brain tumors
- Support for multiple tumor types (glioma, meningioma, pituitary)
- User-friendly web interface for image upload and analysis
- High accuracy brain tumor classification using convolutional neural networks
## 📋 Table of Contents
- [Installation](#-installation)
- [Usage](#-usage)
- [Model](#-model)
- [Dataset](#-dataset)
- [License](#-license)
- [Support](#-support)
- [Contributors](#-contributors-and-developers)
## 🔧 Installation
### Prerequisites
- Python 3.7+
- pip (Python package installer)
### Steps
1. Clone the repository:
```bash
git clone https://github.com/haybnzz/NeuroTumorNet/
cd NeuroTumorNet
```
2. Install required dependencies:
```bash
pip install -r requirements.txt
```
3. Download the pre-trained model:
- Option 1: Download directly from Hugging Face:
```bash
wget "https://huggingface.co/haydenbanz/NeuroTumorNet/resolve/main/brain_tumor_model.h5?download=true" -O brain_tumor_model.h5
```
- Option 2: Use the provided script to download and prepare the model:
```bash
python data_to_model.py
```
- Option 3: Download directly from Kaggle:
### Dataset (Optional)
```bash
Donload from above Badge section
```
If you want to train the model yourself or test it with the original dataset, you can download the brain tumor MRI dataset from the provided data link in the repository.
## Usage
### Running the Web Application
1. After installation, start the web application:
```bash
python app.py
```
2. Open your browser and navigate to:
```
http://localhost:5000
```
3. Upload an MRI image through the web interface to get the tumor classification result.
```
NeuroTumorNet/
├── app.py # Web application for tumor classification
├── data_to_model.py # Script to download and prepare the model
├── requirements.txt # Dependencies list
├── brain_tumor_model.h5 # Pre-trained model file
├
└── README.md # This file
```
## 🧠 Model
NeuroTumorNet uses a deep convolutional neural network architecture designed specifically for medical image classification. The model architecture consists of:
- Multiple convolutional layers with ReLU activation
- Max pooling layers for feature extraction
- Dropout layers to prevent overfitting
- Dense layers for classification
The pre-trained model achieves high accuracy in classifying the four categories of brain MRI images.
## 📊 Dataset
The model was trained on a dataset containing brain MRI images categorized into four classes:
- Glioma tumor
- Meningioma tumor
- Pituitary tumor
- No tumor (normal brain MRI)
To download the dataset for training or testing purposes, visit one of these sources:
- [Kaggle Brain Tumor Dataset](https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset)
- [Figshare Brain Tumor Dataset](https://figshare.com/articles/dataset/brain_tumor_dataset/1512427)
After downloading, place the dataset in a folder named `dataset` with the following structure:
```
dataset/
├── Training/
│ ├── glioma_tumor/
│ ├── meningioma_tumor/
│ ├── no_tumor/
│ └── pituitary_tumor/
└── Testing/
├── glioma_tumor/
├── meningioma_tumor/
├── no_tumor/
└── pituitary_tumor/
```
# Image Display
Here are the images from the repository:
1. 
2. 
3. 
## 📜 License
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. See the [LICENSE](LICENSE) file for more details.
**Unauthorized use is strictly prohibited.**
📧 Contact: [email protected]
## ☕ Support
Donate via Monero: `45PU6txuLxtFFcVP95qT2xXdg7eZzPsqFfbtZp5HTjLbPquDAugBKNSh1bJ76qmAWNGMBCKk4R1UCYqXxYwYfP2wTggZNhq`
## 👥 Contributors and Developers
[
](https://github.com/haybnzz)
[
](https://github.com/Glitchesminds)
## 📝 Citation
If you use NeuroTumorNet in your research, please cite:
```
@software{NeuroTumorNet2025,
author = {Haybnzz and Glitchesminds},
title = {NeuroTumorNet: Deep Learning for Brain Tumor Classification},
url = {https://github.com/haybnzz/NeuroTumorNet},
year = {2025},
}
```
```
@misc {hay.bnz_2025,
author = { {Hay.Bnz} },
title = { NeuroTumorNet (Revision 7f9585f) },
year = 2025,
url = { https://huggingface.co/haydenbanz/NeuroTumorNet },
doi = { 10.57967/hf/4899 },
publisher = { Hugging Face }
}
```
## Acknowledgments
- Thanks to all contributors to the brain tumor MRI datasets used in training this model
- Built with TensorFlow and Keras