aniketp04 / tumornet-gradcam

This repository explores the fascinating world of brain tumor classification using cutting-edge Convolutional Neural Networks (CNNs) and eXplainable Artificial Intelligence (XAI) techniques.

TumorNet-GradCam

This repository explores the fascinating world of brain tumor classification using cutting-edge Convolutional Neural Networks (CNNs) and eXplainable Artificial Intelligence (XAI) techniques.

Dataset

The dataset can be accessed on Kaggle Brain Tumor MRI Dataset.

The dataset to be utilized contains 3,285 brain MRI scan images categorized into four distinct classes: glioma_tumor, meningioma_tumor, pituitary_tumor, and no_tumor.

XAI with Grad-CAM

To make the deep learning model more interpretable and transparent, we implement eXplainable AI (XAI) through the use of Grad-CAM (Gradient-weighted Class Activation Mapping). Grad-CAM helps highlight the regions of the brain images that significantly contribute to the model's classification decisions. This not only aids in model validation but also provides valuable insights to medical professionals.

Glioma Tumor	Meningioma Tumor

No Tumor	Pituitary Tumor