Brain tumors MRI classification through CNN transfer learning models - An Overview

Abstract

One of the most prevalent methods employed in medical research involves identifying brain tumors and monitoring their growth through brain MRI scans. By examining the internal structure of the human brain, valuable insights regarding tumor development can be obtained. However, manually detecting brain tumors from MRI scans poses a significant challenge within the medical research field, as tumors can lead to substantial alterations in both the internal and external brain structure. To address this issue, it is suggested to explore recent classifier approaches for the detection of brain tumors in MRI images. By utilizing these advanced techniques, the performance and analysis of brain tumor growth can be described, enabling the identification of general symptoms and facilitating a targeted diagnosis for an effective treatment plan. This discussion encompasses various classification approaches derived from existing research papers, ultimately leading to conclusive findings on brain tumor detection from MRI scans.