Enhanced Brain Tumor Classification Using Graph Convolutional Neural Network Architecture

This article discusses the use of deep learning and other techniques to automatically classify brain malignancies using brain magnetic resonance images. Mohsen et al. employed the deep learning approach and evaluated the results, while Abd-Ellah et al. presented a two-phase paradigm. Lakshmi and Hemalatha, proposed a two stage Computer Aided System (CAD) that automatically finds out and classifies the BT into different classes using MRI images. Data was first acquired, then image segmented using fuzzy C-means, feature extracted using DWT and Principal component analysis (PCA), and finally tumor classification using DNN.