An Analysis of Brain Tumor Segmentation and Classification Techniques of Deep Learning

Machine Learning plays a critical role in automating tasks that require human wisdom. Although significant studies have been done on segmenting brain tumors using multiple categories of Magnetic Resonance Images, a human evaluator is still required to bridge the semantic gap between the findings of machine learning approaches and those of the human evaluator. The inconsistencies in the shape of the Brain Tumor, as well as its many types and subtypes with varying behaviors, are the reasons behind this. Various strategies for segmenting a brain tumor and extracting characteristics are deeply analyzed in this paper.