A Review of Brain Tumor MRI Classification and Feature Extraction Using Varying Methods

Early detection of brain tumors is critical for saving human lives. MRI is generally used in medical imaging for diagnosing and classifying brain tumors. However, the classification of brain tumors using MRI images is getting more challenging due to the large amount of data and the presence of noise and other objects. Feature extraction is an extremely important step in the brain tumor classification process as it determines the quality of features used for diagnosis. In this work, we examine various feature extraction and classification techniques utilized in MRI image-based brain tumor classification. We have discussed various methods for classification and feature extraction, highlighting the advantages and disadvantages of each. Furthermore, as a result, we analyzed various studies and compared their findings graphically based on performance parameters like accuracy, specificity, and sensitivity. This study's result will be useful for future researchers, providing them with a positive direction towards emerging techniques.