Detection of Brain Tumor from the MRI Images using Deep Hybrid Boosted based on Ensemble Techniques

A brain tumor puts one’s life in danger and interferes with the body’s regular operations. Early identification and treatment planning are essential for a correct diagnosis of a brain tumor. It is crucial to get an early diagnosis of brain tumors in order to increase patient survival and treatment results. Manually assessing the magnetic resonance imaging (MRI) images is challenging. Therefore, more accurate digital approaches for tumor diagnostics are required. Early detection of brain tumors can mean the difference between life and death. Due to their improved performance, deep learning-based brain tumor detection methods have recently attracted attention. However, enormous quantities of classified images are needed to train the deep models in order for these deep learning-based systems to work as predicted. Such data are typically tedious, time-consuming, and prone to human error, which makes it difficult to use such deep learning techniques. Hence, the paper aims to incorporate different ensemble models to show it better than the deep learning algorithms.