A Systematic Review on Brain Mri Classification

Abstract

Magnetic resonance imaging (MRI) is now used to identify brain diseases since it may do so without requiring surgery. The segmentation and classification methods for brain MRI are described in this survey work. MRI was used to classify abnormal and normal tissue based on deep, unsupervised, and supervised learning approaches. Based on the analysis, several assessment criteria are generated and used to support the performance. Lastly, the best method for identifying diseases connected to the brain is a mix of segmentation and classification approaches. Future research will normalize these methods into everyday clinical practice by employing MRI.