An Effective Approach in Brain Tumor Detection and Classification Using CRF

A technical advancement in the medical sector, magnetic resonance imaging (MRI) generates high-quality images the fact that is used to identify and categorize disorders that affect a patient's internal organs. A brain tumor is a particular disorder that is capable of being recognized by examining an MRI image. Medical professionals improve using MRI technology in the early detection of brain tumor disease. The important method for carrying out various tasks like obtaining, pre-processing, extracting useful features, choosing, and classifying MRI images is magnetic resonance imaging analysis. The substance of extraction is a technique for representing an image using its raw data by processing it to extract valuable information that assists with decision-making processes like pattern categorization. Conditional random fields (CRFs) are techniques that are frequently utilized for structured prediction and pattern recognition. MATLAB is used to simulate the suggested system accuracy 90.2%, sensitivity 89.6%, specificity 88%, and produce effective results.