I. Introduction
Magnetic Resonance Imaging (MRI) is a non-invasive, medical imaging that delivers excellent images of the human body and organs in both 2 dimensional (D) and 3D formats [1]. It is widely used and considered to be one of the most accurate techniques for cancer detection and classification, due to its high-resolution images on the brain tissue. It has had a significant influence on the field of automated medical image analysis because of its capacity to deliver a wealth of information on brain anatomy and abnormalities. Tumors may have various shapes and there may not be enough visible landmarks in the image to contribute to an accurate decision. Tumors come in a variety of forms, and there may not be enough apparent markers in the picture to provide an appropriate diagnosis. As a result, it's believed that human diagnosis is inherently unreliable. Furthermore, a misdiagnosis of the kind of brain tumor can be a major problem since it prevents patients from responding well to medical intervention and reduces their chances of survival. On the other hand, an accurate diagnosis will enable the patient to promptly begin the appropriate therapy and live a longer life.