/Brain-Tumor-Detection

Primary LanguageJupyter Notebook

Brain Tumor Detection using CNN

Project Overview

This project aims to detect brain tumors from medical images using a Convolutional Neural Network (CNN). The model is trained on a dataset of over 2000 images and has achieved an accuracy of more than 89%. The CNN model is integrated into a Flask web application, enabling real-time predictions.

Features

  • CNN Model: Developed using TensorFlow/Keras with a focus on accurate tumor detection.
  • Data Augmentation: Applied various augmentation techniques to enhance the dataset and improve model performance.
  • Web Application: Integrated the model with a Flask application for easy accessibility and user interaction.

Technologies Used

  • Python: Programming language for model development.
  • TensorFlow/Keras: Frameworks used for building and training the CNN model.
  • Flask: Web framework for integrating the model into a web application.
  • HTML/CSS: For designing the front-end of the web application.

Installation

Prerequisites

  • Python 3
  • Flask
  • TensorFlow/Keras