Brain Tumor Detection Using VGG-16

Brain Tumour exposes serious medical conditions and threat to human life. Early and accurate detection of these tumours are crucial for effective treatment. In the recent years, deep learning methods are used in medical imaging techniques that have shown promising results in detecting brain tumours. In this study, we proposed to use the Visual Geometry Group (VGG-16) that is based on deep neural network architecture for detecting brain tumours using magnetic resonance images (MRI). The proposed model showed improved result in terms of accuracy. In this work were able. To achieve 96% and 90% accuracy on the training and the testing set respectively with a precision of 96% accuracy on the training set and90% accuracy on the testing set. The recall of the model is also found to be reasonable with a recall of 92% on training set and 88% on the testing set.