A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning

The proposed framework conducts three studies using three architectures of convolutional neural networks (AlexNet, GoogLeNet, and VGGNet) to classify brain tumors such as meningioma, gliomas, and pituitary and achieves highest accuracy up to 98.69 in terms of classification and detection.