Brain Tumor Classification
17/08/2024
Brain Tumor Classification using CNN
This project focuses on the classification of brain tumors using Convolutional Neural Networks (CNNs). The model is trained to differentiate between benign and various types of malignant brain tumors with high accuracy.
Project Overview
Project Overview This project utilizes a deep learning model to classify brain tumors into the following categories: - Benign - Malignant_Pre-B - Malignant_Pro-B - Malignant_early Pre-B The model achieves an accuracy of 98.1% on the test set.
Requirements
Dataset The dataset used in this project includes images of brain tumors that are labeled into the categories mentioned above. Ensure you have the dataset organized and available for training and testing the model. Requirements To run this project, you will need the following libraries and dependencies: - Python 3 - NumPy - Pandas - Matplotlib - Seaborn - Scikit-learn - TensorFlow/Keras
model
model acc and losse
Confusion Matrix
