BrainTumor

Brain Tumor Detection Using MRI Images with CNN and Efficient Net B0

Overview

This repository contains the implementation of a machine learning model for detecting brain tumors from MRI scans. The project utilizes a convolutional neural network (CNN) to classify MRI images into various categories indicating the presence of a tumor.

Project Structure

• brain_tumor_detection.ipynb: The Jupyter notebook contains all the steps from data preprocessing to model evaluation.
• predictions.py: Use this script to load the trained model and make predictions on new MRI images.
• brain.h5: The saved model containing weights and the architecture.
• LICENSE: The license detailing the terms under which this project is shared.

Getting Started

Prerequisites

Before running this project, ensure you have the following installed:

• Python 3.6 or later
• TensorFlow 2.x
• NumPy
• OpenCV
• Matplotlib
• Jupyter Notebook

Installation

Clone the repository and install the required dependencies:

Installation

To set up your environment to run this code, follow the steps below:

git clone https://github.com/<your-github-username>/brain-tumor-detection.git
cd brain-tumor-detection
pip install -r requirements.txt
jupyter notebook brain_tumor_detection.ipynb
python predictions.py