caiodsfelipe/brain-tumor-cnn

This repository contains the code used in the research article titled "An Approach in Brain Tumor Classification: The Development of a New Convolutional Neural Network Model" This study presents a CNN model designed to identify and classify brain tumors from MRI. We used GRAD-CAM to validate our results.

An Approach in Brain Tumor Classification: The Development of a New Convolutional Neural Network Model

This repository contains the code used in the research article titled "An Approach in Brain Tumor Classification: The Development of a New Convolutional Neural Network Model" This study presents a CNN model designed to identify and classify brain tumors from MRI. We used GRAD-CAM to validate our results. For more information, here is the article: https://doi.org/10.5753/eniac.2023.233530

Setup Instructions

1. Clone the repository:

   git clone https://github.com/caiodsfelipe/brain-tumor-cnn.git
   cd brain_tumor_cnn

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv/Scripts/activate`

3. Install the required dependencies:

   pip install -r requirements.txt

4. Set up the environment (e.g., configure Kaggle API key):

   mkdir -p ~/.kaggle
   cp /path/to/your/kaggle.json ~/.kaggle/
   chmod 600 ~/.kaggle/kaggle.json

5. Download and unzip the datasets (assuming the commands in the notebook):

   kaggle datasets download -d masoudnickparvar/brain-tumor-mri-dataset -p data/mri_dataset
   kaggle datasets download -d rahimanshu/figshare-brain-tumor-classification -p data/glioma_dataset
   kaggle datasets download -d sartajbhuvaji/brain-tumor-classification-mri -p data/validation_dataset
   unzip data/mri_dataset/brain-tumor-mri-dataset.zip -d data/mri_dataset
   unzip data/glioma_dataset/figshare-brain-tumor-classification.zip -d data/glioma_dataset
   unzip data/validation_dataset/brain-tumor-classification-mri.zip -d data/validation_dataset

Thats it, now you can use the notebooks/brain_tumor_cnn notebook to run the code!