A Clinical Support System for Brain Tumor Classification Using Soft Computing Techniques

A brain tumor is an accumulation of abnormal cells in human brain. As tumor increases in size, it induces brain damage. Hence it is essential to diagnose the type of brain tumor. The effective modality used for brain tumor diagnose is MRI because of its remarkable image resolution, the speed of acquisition, and high safety profile for patients. The analysis of brain MRI is an important part of patient care and decision. Hence in the proposed Clinical Support System, the brain MRI image is preprocessed using Genetic Optimized Median Filter followed by brain tumor region segmentation using Hierarchical Fuzzy Clustering Algorithm. The features of the tumor region are extracted through GLCM feature extraction method. Lion Optimized Boosting Support Vector machine model is used for further classification of tumor by Brain Tumor Image Segmentation (BraTS) dataset. Hence the proposed clinical support system provides an integrated model for Detection and classification of brain tumor which assists the doctors in appropriate evaluation of tumor.