Investigation of VGG-16, ResNet-50 and AlexNet Performance for Brain Tumor Detection

A brain tumor is a very common and devastating malignant that leads to shorter lifespan if not detected early enough. Brain classification critical step after the has been identified create an effective treatment plan. This study aims investigate three deep learning tools, VGG-16 ResNet50 AlexNet in order detect using MRI images. The results performance are then evaluated compared accuracy, precision recall criteria. dataset used contained 155 images which with tumors, 98 of them non-tumors. model perform extremely well on 96.10% while achieved 94.16% ResNet-50 91.56%. These accuracies positively impact detection tumors before causes physical side effects such as paralysis other disabilities.