Detection and Classification of HGG and LGG Brain Tumor Using Machine Learning

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Abstract

Gliomas are brain tumors starting in the glial cells. Gliomas can be low grade (slow growing) or high grade (fast growing). Physicians use the grade of a brain tumor based on gliomas to decide which treatment a patient needs. The condition of the tumor is of vital importance for the treatment. In this paper, we propose a computerized system to differentiate between normal brain and abnormal brain with tumor in the MRI images and also further classify the abnormal brain tumors into HGG or LGG tumors. The proposed computerized system uses k-means as the segmentation technique for clustering whilst Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) are the main parts of the feature extraction and feature reduction mechanisms, respectively. Support vector machine (SVM) is a major part of our proposed system as it classifies the abnormal brain tumors in the LGG and HGG after the extraction and reduction of the features.