COMPARATIVE EVALUATION OF DIFFERENT METHODS FOR DETECTING BRAIN TUMOR BY USING MAGNETIC RESONANCE IMAGES

A brain tumor impairs the body's ability to operate normally and poses a threat to life. Early brain tumordetection is essential for an accurate diagnosis and effective treatment planning because diagnosis ischallenging, particularly in the early stages of the illness. Conventional methods frequently shorten patients'lives by delaying the necessary medical care. Because the appearance of tumor tissues varies greatly amongpatients and frequently resembles normal tissues, automating this process is a difficult undertaking. MRI is asophisticated medical imaging method that offers a wealth of data regarding the soft-tissue anatomy ofhumans. In the past, several academics have suggested semi-automated and completely automated techniquesfor identifying and classifying brain tumors in this article. Thus, this paper analyzed the literature in astreamlined manner and concentrated on the work of numerous scholars. The main objective of this work is toprovide a comprehensive critical analysis of these studies and findings made in the recent past to detect andclassify brain cancers using MRI scans. Researchers that specialize in deep learning, machine learningtechnologies, neural network etc and wish to use their knowledge to detect and categorize brain tumors willparticularly benefit from this investigation.